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Kako možemo opisati tu razliku?\"},\"tunes\":{}},{\"id\":\"eA7bd_lH4v\",\"type\":\"paragraph\",\"data\":{\"text\":\"Ovaj članak koristi termin Distanca dokaza za udaljenost između tvrdnje i direktno proverljivih dokaza koji je podržavaju.\"},\"tunes\":{}},{\"id\":\"fJX4R85PCt\",\"type\":\"quote\",\"data\":{\"text\":\"Distanca dokaza je broj i snaga transformacija, pretpostavki i inferencijalnih koraka koji razdvajaju tvrdnju od dokaza koji je mogu direktno verifikovati.\",\"caption\":\"Radna definicija — koncept rezonovanja predstavljen ovde, a ne standardizovana metrika.\",\"alignment\":\"left\"},\"tunes\":{}},{\"id\":\"iJ67Av1aSG\",\"type\":\"tableOfContents\",\"data\":{\"title\":\"Contents\",\"minLevel\":2,\"maxLevel\":3},\"tunes\":{}},{\"id\":\"ozmq1MJj3n\",\"type\":\"header\",\"data\":{\"text\":\"Šta to zapravo znači\",\"level\":2},\"tunes\":{}},{\"id\":\"pDKrFaNb6e\",\"type\":\"paragraph\",\"data\":{\"text\":\"Citiranje dokazuje da je izvor referenciran. Ono automatski ne dokazuje da izvor direktno podržava rečenicu pored citata.\"},\"tunes\":{}},{\"id\":\"F1GEb4RZ6l\",\"type\":\"paragraph\",\"data\":{\"text\":\"Između originalnog opažanja i konačnog AI odgovora mogu postojati ekstrakcija, parsiranje, deljenje na delove, pronalaženje, sažimanje, interpretacija, agregacija i zaključivanje.\"},\"tunes\":{}},{\"id\":\"8SfRAwIXCH\",\"type\":\"code\",\"data\":{\"code\":\"Primary evidence\\n   ↓\\nExtracted data\\n   ↓\\nRetrieved passage\\n   ↓\\nSummary\\n   ↓\\nInterpretation\\n   ↓\\nInference\\n   ↓\\nFinal claim\"},\"tunes\":{}},{\"id\":\"EXWtNbQp_o\",\"type\":\"paragraph\",\"data\":{\"text\":\"Svaki korak može biti legitiman. Ali svaki korak takođe može uneti izobličenje.\"},\"tunes\":{}},{\"id\":\"hbM8C-5EyT\",\"type\":\"header\",\"data\":{\"text\":\"Najjednostavniji primer\",\"level\":2},\"tunes\":{}},{\"id\":\"KMGqBiwt4h\",\"type\":\"paragraph\",\"data\":{\"text\":\"Pretpostavimo da temperaturni senzor prijavljuje 38,2 °C.\"},\"tunes\":{}},{\"id\":\"l44ChyK4nK\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Tvrdnja\",\"Odnos prema dokazima\",\"Ilustrativna distanca\"],[\"Senzor prijavljuje 38,2 °C.\",\"Direktno očitavanje\",\"Niska\"],[\"Sistem radi toplije nego juče.\",\"Zahteva poređenje sa jučerašnjim očitavanjem\",\"Umerena\"],[\"Sistem hlađenja otkazuje.\",\"Zahteva kauzalno zaključivanje i alternativna objašnjenja\",\"Visoka\"]]},\"tunes\":{}},{\"id\":\"PojgGe_UNa\",\"type\":\"paragraph\",\"data\":{\"text\":\"Originalna vrednost senzora direktno podržava prvu tvrdnju. Ona sama po sebi ne dokazuje treću.\"},\"tunes\":{}},{\"id\":\"XQGVY-ivLT\",\"type\":\"code\",\"data\":{\"code\":\"Evidence exists\\n        ≠\\nEvidence directly supports every derived claim\"},\"tunes\":{}},{\"id\":\"X69-PNgHPc\",\"type\":\"header\",\"data\":{\"text\":\"Gde primer prestaje da funkcioniše\",\"level\":2},\"tunes\":{}},{\"id\":\"ANwFGAE-nl\",\"type\":\"paragraph\",\"data\":{\"text\":\"Distanca dokaza nije jednostavno brojanje rečenica ili koraka obrade.\"},\"tunes\":{}},{\"id\":\"91yZjN2zid\",\"type\":\"paragraph\",\"data\":{\"text\":\"Jedna matematički validna transformacija može gotovo savršeno sačuvati dokaze, dok jedna spekulativna interpretacija može stvoriti mnogo veći epistemički skok.\"},\"tunes\":{}},{\"id\":\"4XN-TJwp81\",\"type\":\"paragraph\",\"data\":{\"text\":\"Koncept stoga uključuje i distancu po transformaciji i distancu po zaključivanju.\"},\"tunes\":{}},{\"id\":\"SGikOiGH8M\",\"type\":\"header\",\"data\":{\"text\":\"Direktan odgovor\",\"level\":2},\"tunes\":{}},{\"id\":\"4hlBDZFutr\",\"type\":\"paragraph\",\"data\":{\"text\":\"Distanca dokaza se povećava kada tvrdnja zavisi od više transformacija, više pretpostavki, slabijeg porekla ili jače inferencije nego što osnovni dokazi direktno opravdavaju.\"},\"tunes\":{}},{\"id\":\"s2-eCwsoUW\",\"type\":\"code\",\"data\":{\"code\":\"Short distance:\\nsource → claim\\n\\nLonger distance:\\nsource → extraction → summary → assumption → inference → claim\"},\"tunes\":{}},{\"id\":\"Rk86faQsFd\",\"type\":\"paragraph\",\"data\":{\"text\":\"Duža distanca ne čini tvrdnju automatski netačnom. To znači da lanac zaključivanja zahteva više validacije.\"},\"tunes\":{}},{\"id\":\"yZ0DflEzOb\",\"type\":\"header\",\"data\":{\"text\":\"Zašto je ovo važno za AI\",\"level\":2},\"tunes\":{}},{\"id\":\"vOLm2bFaBo\",\"type\":\"paragraph\",\"data\":{\"text\":\"LLM-ovi su posebno dobri u stvaranju tečnih veza između delova informacija. Ta sposobnost je korisna, ali tečnost može sakriti koliko se zaključak udaljio od direktno preuzetih dokaza.\"},\"tunes\":{}},{\"id\":\"C4Si7qSXz1\",\"type\":\"paragraph\",\"data\":{\"text\":\"Odgovor stoga može izgledati dobro potkrepljen dok sadrži tvrdnje čija podrška postoji samo kroz nekoliko neizrečenih inferencijskih koraka.\"},\"tunes\":{}},{\"id\":\"Qh_s1_51GE\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fstajic.de\u002Fsr\u002Fblog\u002Ffrom-research-protocol-to-a-general-ai-reasoning-framework\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Od istraživačkog protokola do opšteg okvira za AI zaključivanje\",\"description\":\"Pouzdano zaključivanje zahteva eksplicitno razdvajanje dokaza, pretpostavki, hipoteza i zaključaka.\"}},\"tunes\":{}},{\"id\":\"bqAXnW2iml\",\"type\":\"header\",\"data\":{\"text\":\"Četiri komponente distance dokaza\",\"level\":2},\"tunes\":{}},{\"id\":\"-Hg9A6A5hp\",\"type\":\"header\",\"data\":{\"text\":\"1. Transformaciona distanca\",\"level\":3},\"tunes\":{}},{\"id\":\"Ihz6V9jHAI\",\"type\":\"paragraph\",\"data\":{\"text\":\"Koliko puta su originalni dokazi konvertovani, sažeti, normalizovani ili preformatirani pre nego što su stigli do modela?\"},\"tunes\":{}},{\"id\":\"Swm-1sbyAn\",\"type\":\"header\",\"data\":{\"text\":\"2. Inferencijska distanca\",\"level\":3},\"tunes\":{}},{\"id\":\"EgovvdsCdI\",\"type\":\"paragraph\",\"data\":{\"text\":\"Koliko je koraka zaključivanja potrebno pre nego što dokazi podrže konačni zaključak?\"},\"tunes\":{}},{\"id\":\"o0cjWpX0nP\",\"type\":\"header\",\"data\":{\"text\":\"3. Distanca porekla\",\"level\":3},\"tunes\":{}},{\"id\":\"_EMlb-CJut\",\"type\":\"paragraph\",\"data\":{\"text\":\"Može li se preuzeta izjava još uvek pratiti do prepoznatljivog originalnog izvora, ili je prošla kroz sažetke i kopije čije je poreklo nejasno?\"},\"tunes\":{}},{\"id\":\"U1UGl3KPLu\",\"type\":\"header\",\"data\":{\"text\":\"4. 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Distanca dokaza pita šta se dešava između tih informacija i tvrdnje koja se na kraju proizvede.\"}},\"tunes\":{}},{\"id\":\"3EV7hEQPBM\",\"type\":\"header\",\"data\":{\"text\":\"Veza sa okidačem za pretragu\",\"level\":2},\"tunes\":{}},{\"id\":\"mzG8UHElAN\",\"type\":\"paragraph\",\"data\":{\"text\":\"Okidač za pretragu pita da li je interno znanje modela dovoljno.\"},\"tunes\":{}},{\"id\":\"aC4UgwxGgp\",\"type\":\"paragraph\",\"data\":{\"text\":\"Distanca dokaza postavlja kasnije pitanje: nakon što su dokazi pronađeni, koliko direktno podržavaju ono što sistem želi da tvrdi?\"},\"tunes\":{}},{\"id\":\"vfMjxGcPan\",\"type\":\"code\",\"data\":{\"code\":\"Need evidence?\\n   ↓\\nRetrieval Trigger\\n   ↓\\nRetrieve\\n   ↓\\nHow directly does evidence support the claim?\\n   ↓\\nEvidence Distance\"},\"tunes\":{}},{\"id\":\"vkrOFgL8vG\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fstajic.de\u002Fsr\u002Fblog\u002Fwhen-should-an-ai-stop-trusting-its-own-knowledge-the-retrieval-trigger\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Kada AI treba da prestane da veruje sopstvenom znanju? — Okidač za pretragu\",\"description\":\"Okidač odlučuje kada su dokazi potrebni. Distanca dokaza procenjuje koliko konačna tvrdnja odmiče od tih dokaza.\"}},\"tunes\":{}},{\"id\":\"AjlyypPDf3\",\"type\":\"header\",\"data\":{\"text\":\"Praktična dijagnostika\",\"level\":2},\"tunes\":{}},{\"id\":\"K4Ypw7YKyJ\",\"type\":\"paragraph\",\"data\":{\"text\":\"Za važnu tvrdnju koju je generisao AI, rekonstruišite lanac podrške unazad.\"},\"tunes\":{}},{\"id\":\"fkjED2EPrm\",\"type\":\"code\",\"data\":{\"code\":\"CLAIM\\n  ↑\\nWhich inference produced it?\\n  ↑\\nWhich retrieved evidence supports that inference?\\n  ↑\\nWhich source produced that evidence?\\n  ↑\\nCan the original source still be inspected?\"},\"tunes\":{}},{\"id\":\"w-7g4lnSZa\",\"type\":\"paragraph\",\"data\":{\"text\":\"Ako se lanac prekine, sistem se suočio sa problemom sledljivosti dokaza.\"},\"tunes\":{}},{\"id\":\"X3AnDUn6WG\",\"type\":\"paragraph\",\"data\":{\"text\":\"Ako lanac ostane netaknut ali zahteva nekoliko jakih pretpostavki, distanca dokaza je i dalje visoka.\"},\"tunes\":{}},{\"id\":\"M36411SDmw\",\"type\":\"header\",\"data\":{\"text\":\"Primer: Podaci o proizvodu\",\"level\":2},\"tunes\":{}},{\"id\":\"2WGPbIKZbE\",\"type\":\"paragraph\",\"data\":{\"text\":\"Pretpostavimo da specifikacija proizvođača kaže da laptop teži 1,48 kg.\"},\"tunes\":{}},{\"id\":\"9XJFwW2i5V\",\"type\":\"code\",\"data\":{\"code\":\"Manufacturer specification\\n→ 1.48 kg\\n→ \\\"The laptop weighs 1.48 kg\\\"\\n\\nLow Evidence Distance\"},\"tunes\":{}},{\"id\":\"roZB_Rua6s\",\"type\":\"paragraph\",\"data\":{\"text\":\"Sada razmotrite:\"},\"tunes\":{}},{\"id\":\"kRstV6Z2C8\",\"type\":\"code\",\"data\":{\"code\":\"Manufacturer specification\\n→ 1.48 kg\\n→ comparison with three competitors\\n→ assumption about travel behavior\\n→ \\\"This is the best laptop for frequent travelers\\\"\\n\\nMuch higher Evidence Distance\"},\"tunes\":{}},{\"id\":\"T7wCeKiXNy\",\"type\":\"paragraph\",\"data\":{\"text\":\"Specifikacija je stvarna. Preporuka je još uvek nekoliko koraka zaključivanja udaljena od nje.\"},\"tunes\":{}},{\"id\":\"2-PNq5WtWj\",\"type\":\"header\",\"data\":{\"text\":\"Primer: Naučni dokazi\",\"level\":2},\"tunes\":{}},{\"id\":\"-pBNIaPz0n\",\"type\":\"paragraph\",\"data\":{\"text\":\"Rad može prijaviti uočenu asocijaciju. AI odgovor to može pogrešno sažeti u kauzalnu izjavu.\"},\"tunes\":{}},{\"id\":\"N9mNiX6VXP\",\"type\":\"code\",\"data\":{\"code\":\"Observed association\\n        ↓\\nInterpretation\\n        ↓\\nUnstated causal assumption\\n        ↓\\n\\\"X causes Y\\\"\"},\"tunes\":{}},{\"id\":\"qj3R7ZB1K2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Problem nije u tome što ne postoje dokazi. Problem je u tome što konačna izjava prelazi veću dokaznu distancu nego što je studija direktno podržava.\"},\"tunes\":{}},{\"id\":\"alhJnubHPy\",\"type\":\"header\",\"data\":{\"text\":\"Veza sa kontekstom spremnim za agente\",\"level\":2},\"tunes\":{}},{\"id\":\"0rREIdIBxs\",\"type\":\"paragraph\",\"data\":{\"text\":\"Strukturirani informacioni objekti mogu smanjiti izbegljivu dokaznu distancu očuvanjem identiteta izvora, jedinica, vremenskih oznaka, konflikata i validnosti umesto prisiljavanja modela da ih rekonstruiše iz spljoštenog teksta.\"},\"tunes\":{}},{\"id\":\"HoxrxiWFMD\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fstajic.de\u002Fsr\u002Fportfolio\u002Ffrom-raw-data-to-verifiable-ai-context-a-practical-architecture-for-agent-ready-information\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Od sirovih podataka do proverljivog AI konteksta: Praktična arhitektura za informacije spremne za agente\",\"description\":\"Očuvanje porekla i validnosti pre preuzimanja smanjuje broj nepodržanih koraka rekonstrukcije potrebnih kasnije.\"}},\"tunes\":{}},{\"id\":\"nQZiY_XXeP\",\"type\":\"header\",\"data\":{\"text\":\"Jednostavna radna skala\",\"level\":2},\"tunes\":{}},{\"id\":\"wYTrrjUzFb\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Nivo\",\"Opis\"],[\"ED0\",\"Direktno prijavljena činjenica iz izvora\"],[\"ED1\",\"Jednostavna deterministička transformacija ili direktno poređenje\"],[\"ED2\",\"Jedan smisleni interpretativni korak\"],[\"ED3\",\"Više pretpostavki ili kombinovanih izvora\"],[\"ED4\",\"Jaka kauzalna, prediktivna ili preskriptivna tvrdnja koja prevazilazi direktne dokaze\"]]},\"tunes\":{}},{\"id\":\"FbEp2L48OB\",\"type\":\"paragraph\",\"data\":{\"text\":\"Ova skala je ilustrativna, a ne naučni standard. Njena svrha je da nametne eksplicitno pitanje: Koliko smo morali dodati između dokaza i tvrdnje?\"},\"tunes\":{}},{\"id\":\"dts_TotX95\",\"type\":\"header\",\"data\":{\"text\":\"Pogrešne predstave\",\"level\":2},\"tunes\":{}},{\"id\":\"3dkxQibpRb\",\"type\":\"paragraph\",\"data\":{\"text\":\"Citiranje znači da je dokazna distanca niska. Ne. Citat može stajati pored tvrdnje koja znatno prevazilazi ono što citirani izvor utvrđuje.\"},\"tunes\":{}},{\"id\":\"x7au6WGUo3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Dugačka dokazna distanca znači da je tvrdnja pogrešna. Ne. Složeni zaključci mogu biti dobro potkrepljeni, ali zahtevaju jači lanac zaključivanja.\"},\"tunes\":{}},{\"id\":\"MuCeBLEinH\",\"type\":\"paragraph\",\"data\":{\"text\":\"Primarni izvori eliminišu zaključivanje. Ne. Primarni dokazi i dalje mogu zahtevati interpretaciju.\"},\"tunes\":{}},{\"id\":\"zDAbJe8M8U\",\"type\":\"paragraph\",\"data\":{\"text\":\"Više izvora automatski smanjuje distancu. Deset slabih ponavljanja iste nepotkrepljene tvrdnje ne stvara direktne dokaze.\"},\"tunes\":{}},{\"id\":\"TP-X-GDBoN\",\"type\":\"header\",\"data\":{\"text\":\"Granični slučaj: Izvedeni podaci\",\"level\":2},\"tunes\":{}},{\"id\":\"BUrXmHPHuz\",\"type\":\"paragraph\",\"data\":{\"text\":\"Neke izvedene vrednosti su pouzdanije od sirovih ljudskih opisa. Ispravno izračunat zbir iz verifikovanih transakcija može biti veoma pouzdan iako je samo jedna transformacija udaljen od originalnih zapisa.\"},\"tunes\":{}},{\"id\":\"wggvCIvsdj\",\"type\":\"paragraph\",\"data\":{\"text\":\"Rastojanje dokaza stoga meri epistemičku razdvojenost, a ne pojednostavljenu sklonost ka netaknutim podacima.\"},\"tunes\":{}},{\"id\":\"RAeAhGUoc1\",\"type\":\"header\",\"data\":{\"text\":\"Ograničenja\",\"level\":2},\"tunes\":{}},{\"id\":\"Fr3MEuEDFC\",\"type\":\"paragraph\",\"data\":{\"text\":\"Rastojanje dokaza je konceptualni dijagnostički alat, a ne univerzalni kvantitativni rezultat.\"},\"tunes\":{}},{\"id\":\"CqEnB7tj9j\",\"type\":\"paragraph\",\"data\":{\"text\":\"Različite oblasti zahtevaju različit tretman zaključivanja. Matematički dokaz, klinički dokazi, softverski dnevnici, analiza tržišta i istorijska interpretacija ne mogu deliti jedan univerzalni numerički prag.\"},\"tunes\":{}},{\"id\":\"rKUMDDmn-_\",\"type\":\"header\",\"data\":{\"text\":\"Šta bi promenilo ovaj odgovor?\",\"level\":2},\"tunes\":{}},{\"id\":\"4MwdAj6jUN\",\"type\":\"paragraph\",\"data\":{\"text\":\"Budući AI sistemi mogu generisati eksplicitne grafove porekla, mašinski proverljive veze tvrdnji i dokaza i tipizirane tragove zaključivanja. To bi moglo učiniti delove Rastojanja dokaza automatski merljivim.\"},\"tunes\":{}},{\"id\":\"mq74gkKLqv\",\"type\":\"paragraph\",\"data\":{\"text\":\"Osnovni problem ostaje: tvrdnja može da se udalji od svojih dokaza čak i dok svaka međukoraka zvuči uverljivo.\"},\"tunes\":{}},{\"id\":\"hxzmVJFI4l\",\"type\":\"header\",\"data\":{\"text\":\"Zaključak\",\"level\":2},\"tunes\":{}},{\"id\":\"Rutv4UON-M\",\"type\":\"paragraph\",\"data\":{\"text\":\"Važna razlika nije samo između odgovora sa izvorima i onih bez izvora.\"},\"tunes\":{}},{\"id\":\"gdAlSpknmL\",\"type\":\"paragraph\",\"data\":{\"text\":\"Ona je između tvrdnji koje ostaju blizu direktno proverljivih dokaza i tvrdnji koje zavise od sve dužih lanaca interpretacije i pretpostavki.\"},\"tunes\":{}},{\"id\":\"QLmqbW5WbP\",\"type\":\"code\",\"data\":{\"code\":\"Evidence\\n   ↓\\nEvidence Distance\\n   ↓\\nReasoning\\n   ↓\\nAnswer Validity Boundary\"},\"tunes\":{}},{\"id\":\"e5dRr-RLD3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Rastojanje dokaza nam daje jezik za opisivanje tog prostora.\"},\"tunes\":{}},{\"id\":\"03za6O-xj4\",\"type\":\"header\",\"data\":{\"text\":\"Primarni izvori\",\"level\":2},\"tunes\":{}},{\"id\":\"qkhP_PbKj7\",\"type\":\"paragraph\",\"data\":{\"text\":\"Patrick Lewis et al., \u003Ca href=\\\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2005.11401\\\" target=\\\"_blank\\\">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks\u003C\u002Fa> (2020).\"},\"tunes\":{}},{\"id\":\"3LtuUX7bLn\",\"type\":\"paragraph\",\"data\":{\"text\":\"Nelson F. Liu et al., \u003Ca href=\\\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.03172\\\" target=\\\"_blank\\\">Lost in the Middle: How Language Models Use Long Contexts\u003C\u002Fa> (2023).\"},\"tunes\":{}},{\"id\":\"4cqBoslndX\",\"type\":\"paragraph\",\"data\":{\"text\":\"W3C, \u003Ca href=\\\"https:\u002F\u002Fwww.w3.org\u002FTR\u002Fprov-overview\u002F\\\" target=\\\"_blank\\\">PROV Overview\u003C\u002Fa>. Standardizovani model za predstavljanje odnosa porekla.\"},\"tunes\":{}}],\"version\":\"2.31.6\"}",{"time":228,"blocks":229,"version":740},1792096924190,[230,236,242,247,255,262,267,272,277,283,288,293,298,320,325,330,335,340,345,350,355,360,365,370,375,380,385,396,401,406,411,416,421,426,431,436,441,446,451,456,461,470,475,480,485,490,499,504,509,514,519,524,529,534,539,544,549,554,559,564,569,574,579,584,592,597,620,625,630,635,640,645,650,655,660,665,670,675,680,685,690,695,700,705,710,715,720,725,730,735],{"id":231,"data":232,"type":42,"tunes":235},"iotBWJJ4uZ",{"text":233,"level":234},"Pitanje",2,{},{"id":237,"data":238,"type":240,"tunes":241},"RuWcV0R1yx",{"text":239},"Dva AI odgovora mogu oba citirati izvore i ipak se znatno razlikovati u tome koliko direktno ti izvori podržavaju tvrdnje koje se iznose. Kako možemo opisati tu razliku?","paragraph",{},{"id":243,"data":244,"type":240,"tunes":246},"eA7bd_lH4v",{"text":245},"Ovaj članak koristi termin Distanca dokaza za udaljenost između tvrdnje i direktno proverljivih dokaza koji je podržavaju.",{},{"id":248,"data":249,"type":253,"tunes":254},"fJX4R85PCt",{"text":250,"caption":251,"alignment":252},"Distanca dokaza je broj i snaga transformacija, pretpostavki i inferencijalnih koraka koji razdvajaju tvrdnju od dokaza koji je mogu direktno verifikovati.","Radna definicija — koncept rezonovanja predstavljen ovde, a ne standardizovana metrika.","left","quote",{},{"id":256,"data":257,"type":260,"tunes":261},"iJ67Av1aSG",{"title":258,"maxLevel":259,"minLevel":234},"Contents",3,"tableOfContents",{},{"id":263,"data":264,"type":42,"tunes":266},"ozmq1MJj3n",{"text":265,"level":234},"Šta to zapravo znači",{},{"id":268,"data":269,"type":240,"tunes":271},"pDKrFaNb6e",{"text":270},"Citiranje dokazuje da je izvor referenciran. Ono automatski ne dokazuje da izvor direktno podržava rečenicu pored citata.",{},{"id":273,"data":274,"type":240,"tunes":276},"F1GEb4RZ6l",{"text":275},"Između originalnog opažanja i konačnog AI odgovora mogu postojati ekstrakcija, parsiranje, deljenje na delove, pronalaženje, sažimanje, interpretacija, agregacija i zaključivanje.",{},{"id":278,"data":279,"type":281,"tunes":282},"8SfRAwIXCH",{"code":280},"Primary evidence\n   ↓\nExtracted data\n   ↓\nRetrieved passage\n   ↓\nSummary\n   ↓\nInterpretation\n   ↓\nInference\n   ↓\nFinal claim","code",{},{"id":284,"data":285,"type":240,"tunes":287},"EXWtNbQp_o",{"text":286},"Svaki korak može biti legitiman. Ali svaki korak takođe može uneti izobličenje.",{},{"id":289,"data":290,"type":42,"tunes":292},"hbM8C-5EyT",{"text":291,"level":234},"Najjednostavniji primer",{},{"id":294,"data":295,"type":240,"tunes":297},"KMGqBiwt4h",{"text":296},"Pretpostavimo da temperaturni senzor prijavljuje 38,2 °C.",{},{"id":299,"data":300,"type":318,"tunes":319},"l44ChyK4nK",{"content":301,"stretched":43,"withHeadings":14},[302,306,310,314],[303,304,305],"Tvrdnja","Odnos prema dokazima","Ilustrativna distanca",[307,308,309],"Senzor prijavljuje 38,2 °C.","Direktno očitavanje","Niska",[311,312,313],"Sistem radi toplije nego juče.","Zahteva poređenje sa jučerašnjim očitavanjem","Umerena",[315,316,317],"Sistem hlađenja otkazuje.","Zahteva kauzalno zaključivanje i alternativna objašnjenja","Visoka","table",{},{"id":321,"data":322,"type":240,"tunes":324},"PojgGe_UNa",{"text":323},"Originalna vrednost senzora direktno podržava prvu tvrdnju. Ona sama po sebi ne dokazuje treću.",{},{"id":326,"data":327,"type":281,"tunes":329},"XQGVY-ivLT",{"code":328},"Evidence exists\n        ≠\nEvidence directly supports every derived claim",{},{"id":331,"data":332,"type":42,"tunes":334},"X69-PNgHPc",{"text":333,"level":234},"Gde primer prestaje da funkcioniše",{},{"id":336,"data":337,"type":240,"tunes":339},"ANwFGAE-nl",{"text":338},"Distanca dokaza nije jednostavno brojanje rečenica ili koraka obrade.",{},{"id":341,"data":342,"type":240,"tunes":344},"91yZjN2zid",{"text":343},"Jedna matematički validna transformacija može gotovo savršeno sačuvati dokaze, dok jedna spekulativna interpretacija može stvoriti mnogo veći epistemički skok.",{},{"id":346,"data":347,"type":240,"tunes":349},"4XN-TJwp81",{"text":348},"Koncept stoga uključuje i distancu po transformaciji i distancu po zaključivanju.",{},{"id":351,"data":352,"type":42,"tunes":354},"SGikOiGH8M",{"text":353,"level":234},"Direktan odgovor",{},{"id":356,"data":357,"type":240,"tunes":359},"4hlBDZFutr",{"text":358},"Distanca dokaza se povećava kada tvrdnja zavisi od više transformacija, više pretpostavki, slabijeg porekla ili jače inferencije nego što osnovni dokazi direktno opravdavaju.",{},{"id":361,"data":362,"type":281,"tunes":364},"s2-eCwsoUW",{"code":363},"Short distance:\nsource → claim\n\nLonger distance:\nsource → extraction → summary → assumption → inference → claim",{},{"id":366,"data":367,"type":240,"tunes":369},"Rk86faQsFd",{"text":368},"Duža distanca ne čini tvrdnju automatski netačnom. To znači da lanac zaključivanja zahteva više validacije.",{},{"id":371,"data":372,"type":42,"tunes":374},"yZ0DflEzOb",{"text":373,"level":234},"Zašto je ovo važno za AI",{},{"id":376,"data":377,"type":240,"tunes":379},"vOLm2bFaBo",{"text":378},"LLM-ovi su posebno dobri u stvaranju tečnih veza između delova informacija. Ta sposobnost je korisna, ali tečnost može sakriti koliko se zaključak udaljio od direktno preuzetih dokaza.",{},{"id":381,"data":382,"type":240,"tunes":384},"C4Si7qSXz1",{"text":383},"Odgovor stoga može izgledati dobro potkrepljen dok sadrži tvrdnje čija podrška postoji samo kroz nekoliko neizrečenih inferencijskih koraka.",{},{"id":386,"data":387,"type":394,"tunes":395},"Qh_s1_51GE",{"link":388,"meta":389},"https:\u002F\u002Fstajic.de\u002Fsr\u002Fblog\u002Ffrom-research-protocol-to-a-general-ai-reasoning-framework",{"image":390,"title":392,"description":393},{"url":391},"","Od istraživačkog protokola do opšteg okvira za AI zaključivanje","Pouzdano zaključivanje zahteva eksplicitno razdvajanje dokaza, pretpostavki, hipoteza i zaključaka.","linkTool",{},{"id":397,"data":398,"type":42,"tunes":400},"bqAXnW2iml",{"text":399,"level":234},"Četiri komponente distance dokaza",{},{"id":402,"data":403,"type":42,"tunes":405},"-Hg9A6A5hp",{"text":404,"level":259},"1. Transformaciona distanca",{},{"id":407,"data":408,"type":240,"tunes":410},"Ihz6V9jHAI",{"text":409},"Koliko puta su originalni dokazi konvertovani, sažeti, normalizovani ili preformatirani pre nego što su stigli do modela?",{},{"id":412,"data":413,"type":42,"tunes":415},"Swm-1sbyAn",{"text":414,"level":259},"2. Inferencijska distanca",{},{"id":417,"data":418,"type":240,"tunes":420},"EgovvdsCdI",{"text":419},"Koliko je koraka zaključivanja potrebno pre nego što dokazi podrže konačni zaključak?",{},{"id":422,"data":423,"type":42,"tunes":425},"o0cjWpX0nP",{"text":424,"level":259},"3. Distanca porekla",{},{"id":427,"data":428,"type":240,"tunes":430},"_EMlb-CJut",{"text":429},"Može li se preuzeta izjava još uvek pratiti do prepoznatljivog originalnog izvora, ili je prošla kroz sažetke i kopije čije je poreklo nejasno?",{},{"id":432,"data":433,"type":42,"tunes":435},"U1UGl3KPLu",{"text":434,"level":259},"4. Distanca primenljivosti",{},{"id":437,"data":438,"type":240,"tunes":440},"SUo3t92ekw",{"text":439},"Koliko je zaključivanja potrebno da bi se utvrdilo da se dokazi odnose na ovu tačnu verziju, korisnika, jurisdikciju, vremenski period ili situaciju?",{},{"id":442,"data":443,"type":42,"tunes":445},"YaznjEJ8WC",{"text":444,"level":234},"Distanca dokaza u RAG-u",{},{"id":447,"data":448,"type":240,"tunes":450},"4GiJAnL8nj",{"text":449},"RAG može skratiti jednu važnu distancu: distancu između modela i eksternog znanja.",{},{"id":452,"data":453,"type":240,"tunes":455},"_eiLv8z7zh",{"text":454},"Ne skraćuje automatski distancu između pronađenog odlomka i konačne tvrdnje.",{},{"id":457,"data":458,"type":281,"tunes":460},"e8Bu2r5MO7",{"code":459},"RAG solves:\nmodel ↔ external information\n\nRAG does not automatically solve:\nevidence ↔ justified conclusion",{},{"id":462,"data":463,"type":394,"tunes":469},"5DxUvb-LJ0",{"link":464,"meta":465},"https:\u002F\u002Fstajic.de\u002Fsr\u002Fblog\u002Fwhere-does-an-llm-get-its-data-rag-data-sources-in-python",{"image":466,"title":467,"description":468},{"url":391},"Odakle LLM dobija svoje podatke? RAG izvori podataka u Python-u","Pretraga unosi eksterne informacije u kontekst. Distanca dokaza pita šta se dešava između tih informacija i tvrdnje koja se na kraju proizvede.",{},{"id":471,"data":472,"type":42,"tunes":474},"3EV7hEQPBM",{"text":473,"level":234},"Veza sa okidačem za pretragu",{},{"id":476,"data":477,"type":240,"tunes":479},"mzG8UHElAN",{"text":478},"Okidač za pretragu pita da li je interno znanje modela dovoljno.",{},{"id":481,"data":482,"type":240,"tunes":484},"aC4UgwxGgp",{"text":483},"Distanca dokaza postavlja kasnije pitanje: nakon što su dokazi pronađeni, koliko direktno podržavaju ono što sistem želi da tvrdi?",{},{"id":486,"data":487,"type":281,"tunes":489},"vfMjxGcPan",{"code":488},"Need evidence?\n   ↓\nRetrieval Trigger\n   ↓\nRetrieve\n   ↓\nHow directly does evidence support the claim?\n   ↓\nEvidence Distance",{},{"id":491,"data":492,"type":394,"tunes":498},"vkrOFgL8vG",{"link":493,"meta":494},"https:\u002F\u002Fstajic.de\u002Fsr\u002Fblog\u002Fwhen-should-an-ai-stop-trusting-its-own-knowledge-the-retrieval-trigger",{"image":495,"title":496,"description":497},{"url":391},"Kada AI treba da prestane da veruje sopstvenom znanju? — Okidač za pretragu","Okidač odlučuje kada su dokazi potrebni. Distanca dokaza procenjuje koliko konačna tvrdnja odmiče od tih dokaza.",{},{"id":500,"data":501,"type":42,"tunes":503},"AjlyypPDf3",{"text":502,"level":234},"Praktična dijagnostika",{},{"id":505,"data":506,"type":240,"tunes":508},"K4Ypw7YKyJ",{"text":507},"Za važnu tvrdnju koju je generisao AI, rekonstruišite lanac podrške unazad.",{},{"id":510,"data":511,"type":281,"tunes":513},"fkjED2EPrm",{"code":512},"CLAIM\n  ↑\nWhich inference produced it?\n  ↑\nWhich retrieved evidence supports that inference?\n  ↑\nWhich source produced that evidence?\n  ↑\nCan the original source still be inspected?",{},{"id":515,"data":516,"type":240,"tunes":518},"w-7g4lnSZa",{"text":517},"Ako se lanac prekine, sistem se suočio sa problemom sledljivosti dokaza.",{},{"id":520,"data":521,"type":240,"tunes":523},"X3AnDUn6WG",{"text":522},"Ako lanac ostane netaknut ali zahteva nekoliko jakih pretpostavki, distanca dokaza je i dalje visoka.",{},{"id":525,"data":526,"type":42,"tunes":528},"M36411SDmw",{"text":527,"level":234},"Primer: Podaci o proizvodu",{},{"id":530,"data":531,"type":240,"tunes":533},"2WGPbIKZbE",{"text":532},"Pretpostavimo da specifikacija proizvođača kaže da laptop teži 1,48 kg.",{},{"id":535,"data":536,"type":281,"tunes":538},"9XJFwW2i5V",{"code":537},"Manufacturer specification\n→ 1.48 kg\n→ \"The laptop weighs 1.48 kg\"\n\nLow Evidence Distance",{},{"id":540,"data":541,"type":240,"tunes":543},"roZB_Rua6s",{"text":542},"Sada razmotrite:",{},{"id":545,"data":546,"type":281,"tunes":548},"kRstV6Z2C8",{"code":547},"Manufacturer specification\n→ 1.48 kg\n→ comparison with three competitors\n→ assumption about travel behavior\n→ \"This is the best laptop for frequent travelers\"\n\nMuch higher Evidence Distance",{},{"id":550,"data":551,"type":240,"tunes":553},"T7wCeKiXNy",{"text":552},"Specifikacija je stvarna. Preporuka je još uvek nekoliko koraka zaključivanja udaljena od nje.",{},{"id":555,"data":556,"type":42,"tunes":558},"2-PNq5WtWj",{"text":557,"level":234},"Primer: Naučni dokazi",{},{"id":560,"data":561,"type":240,"tunes":563},"-pBNIaPz0n",{"text":562},"Rad može prijaviti uočenu asocijaciju. AI odgovor to može pogrešno sažeti u kauzalnu izjavu.",{},{"id":565,"data":566,"type":281,"tunes":568},"N9mNiX6VXP",{"code":567},"Observed association\n        ↓\nInterpretation\n        ↓\nUnstated causal assumption\n        ↓\n\"X causes Y\"",{},{"id":570,"data":571,"type":240,"tunes":573},"qj3R7ZB1K2",{"text":572},"Problem nije u tome što ne postoje dokazi. Problem je u tome što konačna izjava prelazi veću dokaznu distancu nego što je studija direktno podržava.",{},{"id":575,"data":576,"type":42,"tunes":578},"alhJnubHPy",{"text":577,"level":234},"Veza sa kontekstom spremnim za agente",{},{"id":580,"data":581,"type":240,"tunes":583},"0rREIdIBxs",{"text":582},"Strukturirani informacioni objekti mogu smanjiti izbegljivu dokaznu distancu očuvanjem identiteta izvora, jedinica, vremenskih oznaka, konflikata i validnosti umesto prisiljavanja modela da ih rekonstruiše iz spljoštenog teksta.",{},{"id":585,"data":586,"type":394,"tunes":591},"HoxrxiWFMD",{"link":587,"meta":588},"https:\u002F\u002Fstajic.de\u002Fsr\u002Fportfolio\u002Ffrom-raw-data-to-verifiable-ai-context-a-practical-architecture-for-agent-ready-information",{"image":589,"title":184,"description":590},{"url":391},"Očuvanje porekla i validnosti pre preuzimanja smanjuje broj nepodržanih koraka rekonstrukcije potrebnih kasnije.",{},{"id":593,"data":594,"type":42,"tunes":596},"nQZiY_XXeP",{"text":595,"level":234},"Jednostavna radna skala",{},{"id":598,"data":599,"type":318,"tunes":619},"wYTrrjUzFb",{"content":600,"stretched":43,"withHeadings":14},[601,604,607,610,613,616],[602,603],"Nivo","Opis",[605,606],"ED0","Direktno prijavljena činjenica iz izvora",[608,609],"ED1","Jednostavna deterministička transformacija ili direktno poređenje",[611,612],"ED2","Jedan smisleni interpretativni korak",[614,615],"ED3","Više pretpostavki ili kombinovanih izvora",[617,618],"ED4","Jaka kauzalna, prediktivna ili preskriptivna tvrdnja koja prevazilazi direktne dokaze",{},{"id":621,"data":622,"type":240,"tunes":624},"FbEp2L48OB",{"text":623},"Ova skala je ilustrativna, a ne naučni standard. Njena svrha je da nametne eksplicitno pitanje: Koliko smo morali dodati između dokaza i tvrdnje?",{},{"id":626,"data":627,"type":42,"tunes":629},"dts_TotX95",{"text":628,"level":234},"Pogrešne predstave",{},{"id":631,"data":632,"type":240,"tunes":634},"3dkxQibpRb",{"text":633},"Citiranje znači da je dokazna distanca niska. Ne. Citat može stajati pored tvrdnje koja znatno prevazilazi ono što citirani izvor utvrđuje.",{},{"id":636,"data":637,"type":240,"tunes":639},"x7au6WGUo3",{"text":638},"Dugačka dokazna distanca znači da je tvrdnja pogrešna. Ne. Složeni zaključci mogu biti dobro potkrepljeni, ali zahtevaju jači lanac zaključivanja.",{},{"id":641,"data":642,"type":240,"tunes":644},"MuCeBLEinH",{"text":643},"Primarni izvori eliminišu zaključivanje. Ne. Primarni dokazi i dalje mogu zahtevati interpretaciju.",{},{"id":646,"data":647,"type":240,"tunes":649},"zDAbJe8M8U",{"text":648},"Više izvora automatski smanjuje distancu. Deset slabih ponavljanja iste nepotkrepljene tvrdnje ne stvara direktne dokaze.",{},{"id":651,"data":652,"type":42,"tunes":654},"TP-X-GDBoN",{"text":653,"level":234},"Granični slučaj: Izvedeni podaci",{},{"id":656,"data":657,"type":240,"tunes":659},"BUrXmHPHuz",{"text":658},"Neke izvedene vrednosti su pouzdanije od sirovih ljudskih opisa. Ispravno izračunat zbir iz verifikovanih transakcija može biti veoma pouzdan iako je samo jedna transformacija udaljen od originalnih zapisa.",{},{"id":661,"data":662,"type":240,"tunes":664},"wggvCIvsdj",{"text":663},"Rastojanje dokaza stoga meri epistemičku razdvojenost, a ne pojednostavljenu sklonost ka netaknutim podacima.",{},{"id":666,"data":667,"type":42,"tunes":669},"RAeAhGUoc1",{"text":668,"level":234},"Ograničenja",{},{"id":671,"data":672,"type":240,"tunes":674},"Fr3MEuEDFC",{"text":673},"Rastojanje dokaza je konceptualni dijagnostički alat, a ne univerzalni kvantitativni rezultat.",{},{"id":676,"data":677,"type":240,"tunes":679},"CqEnB7tj9j",{"text":678},"Različite oblasti zahtevaju različit tretman zaključivanja. Matematički dokaz, klinički dokazi, softverski dnevnici, analiza tržišta i istorijska interpretacija ne mogu deliti jedan univerzalni numerički prag.",{},{"id":681,"data":682,"type":42,"tunes":684},"rKUMDDmn-_",{"text":683,"level":234},"Šta bi promenilo ovaj odgovor?",{},{"id":686,"data":687,"type":240,"tunes":689},"4MwdAj6jUN",{"text":688},"Budući AI sistemi mogu generisati eksplicitne grafove porekla, mašinski proverljive veze tvrdnji i dokaza i tipizirane tragove zaključivanja. To bi moglo učiniti delove Rastojanja dokaza automatski merljivim.",{},{"id":691,"data":692,"type":240,"tunes":694},"mq74gkKLqv",{"text":693},"Osnovni problem ostaje: tvrdnja može da se udalji od svojih dokaza čak i dok svaka međukoraka zvuči uverljivo.",{},{"id":696,"data":697,"type":42,"tunes":699},"hxzmVJFI4l",{"text":698,"level":234},"Zaključak",{},{"id":701,"data":702,"type":240,"tunes":704},"Rutv4UON-M",{"text":703},"Važna razlika nije samo između odgovora sa izvorima i onih bez izvora.",{},{"id":706,"data":707,"type":240,"tunes":709},"gdAlSpknmL",{"text":708},"Ona je između tvrdnji koje ostaju blizu direktno proverljivih dokaza i tvrdnji koje zavise od sve dužih lanaca interpretacije i pretpostavki.",{},{"id":711,"data":712,"type":281,"tunes":714},"QLmqbW5WbP",{"code":713},"Evidence\n   ↓\nEvidence Distance\n   ↓\nReasoning\n   ↓\nAnswer Validity Boundary",{},{"id":716,"data":717,"type":240,"tunes":719},"e5dRr-RLD3",{"text":718},"Rastojanje dokaza nam daje jezik za opisivanje tog prostora.",{},{"id":721,"data":722,"type":42,"tunes":724},"03za6O-xj4",{"text":723,"level":234},"Primarni izvori",{},{"id":726,"data":727,"type":240,"tunes":729},"qkhP_PbKj7",{"text":728},"Patrick Lewis et al., \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2005.11401\" target=\"_blank\">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks\u003C\u002Fa> (2020).",{},{"id":731,"data":732,"type":240,"tunes":734},"3LtuUX7bLn",{"text":733},"Nelson F. Liu et al., \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.03172\" target=\"_blank\">Lost in the Middle: How Language Models Use Long Contexts\u003C\u002Fa> (2023).",{},{"id":736,"data":737,"type":240,"tunes":739},"4cqBoslndX",{"text":738},"W3C, \u003Ca href=\"https:\u002F\u002Fwww.w3.org\u002FTR\u002Fprov-overview\u002F\" target=\"_blank\">PROV Overview\u003C\u002Fa>. Standardizovani model za predstavljanje odnosa porekla.",{},"2.31.6","Nisu svi podržani odgovori podjednako blizu svojim dokazima. Udaljenost dokaza je praktičan način da se opiše koliko transformacija, sažetaka, pretpostavki i koraka zaključivanja razdvaja tvrdnju AI od direktno proverljivih dokaza.","\u002Fuploads\u002F2026\u002F10\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance-1792095863209-3c1mog.webp","how-far-is-an-ai-claim-from-the-evidence-evidence-distance-1792095863209-3c1mog","PUBLISHED","2026-10-15T00:23:00.000Z","2026-10-15T20:23:08.634Z","2026-10-15T20:43:52.893Z",{"en":749,"de":750,"sr":751,"es":752,"fr":753,"it":754,"ru":755,"zh":756},"\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance","\u002Fde\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance","\u002Fsr\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance","\u002Fes\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance","\u002Ffr\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance","\u002Fit\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance","\u002Fru\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance","\u002Fzh\u002Fblog\u002Fhow-far-is-an-ai-claim-from-the-evidence-evidence-distance",[758,762],{"id":759,"name":760,"slug":761},68,"Rizici, kontrole i dokazi","risks-and-controls",{"id":763,"name":764,"slug":765},49,"Kontrole i dokazi","controls",{"id":767,"login":768,"email":391,"displayName":769},"20","rooth8233","Aleksandar Stajić",[771,1262],{"lang":772,"title":773,"content":774,"contentJson":775,"excerpt":1261},"en","How Far Is an AI Claim From the Evidence? — Evidence Distance","{\"time\":1792096795538,\"blocks\":[{\"id\":\"g-2Ciyj8LJ\",\"type\":\"header\",\"data\":{\"text\":\"Question\",\"level\":2},\"tunes\":{}},{\"id\":\"SQWD7UraiX\",\"type\":\"paragraph\",\"data\":{\"text\":\"Two AI answers can both cite sources and still differ greatly in how directly those sources support the claims being made. How can we describe that difference?\"},\"tunes\":{}},{\"id\":\"Sj1fx2865j\",\"type\":\"paragraph\",\"data\":{\"text\":\"This article uses the term Evidence Distance for the distance between a claim and the directly inspectable evidence that supports it.\"},\"tunes\":{}},{\"id\":\"d5th-A-mq5\",\"type\":\"quote\",\"data\":{\"text\":\"Evidence Distance is the number and strength of transformations, assumptions and inferential steps separating a claim from the evidence that can directly verify it.\",\"caption\":\"Working definition — a reasoning concept introduced here, not a standardized metric.\",\"alignment\":\"left\"},\"tunes\":{}},{\"id\":\"X81jXC72FC\",\"type\":\"tableOfContents\",\"data\":{\"title\":\"Contents\",\"minLevel\":2,\"maxLevel\":3},\"tunes\":{}},{\"id\":\"_pZcnPEoil\",\"type\":\"header\",\"data\":{\"text\":\"What This Really Means\",\"level\":2},\"tunes\":{}},{\"id\":\"F5odO7xyha\",\"type\":\"paragraph\",\"data\":{\"text\":\"A citation proves that a source was referenced. It does not automatically prove that the source directly supports the sentence beside the citation.\"},\"tunes\":{}},{\"id\":\"8Gqlg-ArJS\",\"type\":\"paragraph\",\"data\":{\"text\":\"Between an original observation and a final AI answer there may be extraction, parsing, chunking, retrieval, summarization, interpretation, aggregation and inference.\"},\"tunes\":{}},{\"id\":\"lXkL5LV9ab\",\"type\":\"code\",\"data\":{\"code\":\"Primary evidence\\n   ↓\\nExtracted data\\n   ↓\\nRetrieved passage\\n   ↓\\nSummary\\n   ↓\\nInterpretation\\n   ↓\\nInference\\n   ↓\\nFinal claim\"},\"tunes\":{}},{\"id\":\"Z-8GPQIpCI\",\"type\":\"paragraph\",\"data\":{\"text\":\"Every step can be legitimate. But every step can also introduce distortion.\"},\"tunes\":{}},{\"id\":\"aXMwTGZ8Ia\",\"type\":\"header\",\"data\":{\"text\":\"Simplest Example\",\"level\":2},\"tunes\":{}},{\"id\":\"bZlU7KD3M2\",\"type\":\"paragraph\",\"data\":{\"text\":\"Suppose a temperature sensor reports 38.2 °C.\"},\"tunes\":{}},{\"id\":\"SP87UUPaU3\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Claim\",\"Relationship to evidence\",\"Illustrative distance\"],[\"The sensor reports 38.2 °C.\",\"Direct reading\",\"Low\"],[\"The system is running hotter than yesterday.\",\"Requires comparison with yesterday's reading\",\"Moderate\"],[\"The cooling system is failing.\",\"Requires causal inference and alternative explanations\",\"High\"]]},\"tunes\":{}},{\"id\":\"eYar059d69\",\"type\":\"paragraph\",\"data\":{\"text\":\"The original sensor value directly supports the first claim. It does not by itself prove the third.\"},\"tunes\":{}},{\"id\":\"eCnFlByvHt\",\"type\":\"code\",\"data\":{\"code\":\"Evidence exists\\n        ≠\\nEvidence directly supports every derived claim\"},\"tunes\":{}},{\"id\":\"aXGkK6BpkF\",\"type\":\"header\",\"data\":{\"text\":\"Where the Example Stops Working\",\"level\":2},\"tunes\":{}},{\"id\":\"lAwb9QZ_yB\",\"type\":\"paragraph\",\"data\":{\"text\":\"Evidence Distance is not simply a count of sentences or processing steps.\"},\"tunes\":{}},{\"id\":\"-SzYko9oIH\",\"type\":\"paragraph\",\"data\":{\"text\":\"One mathematically valid transformation may preserve evidence almost perfectly, while a single speculative interpretation may create a much larger epistemic jump.\"},\"tunes\":{}},{\"id\":\"XOQloBndLw\",\"type\":\"paragraph\",\"data\":{\"text\":\"The concept therefore includes both distance by transformation and distance by inference.\"},\"tunes\":{}},{\"id\":\"EOXbS4TAOR\",\"type\":\"header\",\"data\":{\"text\":\"Direct Answer\",\"level\":2},\"tunes\":{}},{\"id\":\"HcVL8vGM74\",\"type\":\"paragraph\",\"data\":{\"text\":\"Evidence Distance increases when a claim depends on more transformations, more assumptions, weaker provenance or stronger inference than the underlying evidence directly warrants.\"},\"tunes\":{}},{\"id\":\"_f7WXjUOsS\",\"type\":\"code\",\"data\":{\"code\":\"Short distance:\\nsource → claim\\n\\nLonger distance:\\nsource → extraction → summary → assumption → inference → claim\"},\"tunes\":{}},{\"id\":\"zUEC-cDhqm\",\"type\":\"paragraph\",\"data\":{\"text\":\"A longer distance does not automatically make a claim false. It means the reasoning chain requires more validation.\"},\"tunes\":{}},{\"id\":\"ix7TUGNz_W\",\"type\":\"header\",\"data\":{\"text\":\"Why This Matters for AI\",\"level\":2},\"tunes\":{}},{\"id\":\"wrAy5PLtLB\",\"type\":\"paragraph\",\"data\":{\"text\":\"LLMs are particularly good at producing fluent bridges between pieces of information. That capability is useful, but fluency can hide how far the conclusion has moved beyond the directly retrieved evidence.\"},\"tunes\":{}},{\"id\":\"jJseLuTWdv\",\"type\":\"paragraph\",\"data\":{\"text\":\"An answer can therefore look well sourced while containing claims whose support exists only through several unstated inferential steps.\"},\"tunes\":{}},{\"id\":\"ox8fok9dzs\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fstajic.de\u002Fblog\u002Ffrom-research-protocol-to-a-general-ai-reasoning-framework\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"From Research Protocol to a General AI Reasoning Framework\",\"description\":\"Reliable reasoning requires explicit separation of evidence, assumptions, hypotheses and conclusions.\"}},\"tunes\":{}},{\"id\":\"6ipse6YG1U\",\"type\":\"header\",\"data\":{\"text\":\"Four Components of Evidence Distance\",\"level\":2},\"tunes\":{}},{\"id\":\"P4xQ7o96dR\",\"type\":\"header\",\"data\":{\"text\":\"1. Transformation Distance\",\"level\":3},\"tunes\":{}},{\"id\":\"dvN8TUNEYG\",\"type\":\"paragraph\",\"data\":{\"text\":\"How many times has the original evidence been converted, summarized, normalized or reformatted before reaching the model?\"},\"tunes\":{}},{\"id\":\"dXofACF9_x\",\"type\":\"header\",\"data\":{\"text\":\"2. Inferential Distance\",\"level\":3},\"tunes\":{}},{\"id\":\"kkEzV3ydId\",\"type\":\"paragraph\",\"data\":{\"text\":\"How many reasoning steps are required before the evidence supports the final conclusion?\"},\"tunes\":{}},{\"id\":\"PPYB0RuX5_\",\"type\":\"header\",\"data\":{\"text\":\"3. Provenance Distance\",\"level\":3},\"tunes\":{}},{\"id\":\"cAVBYebJr7\",\"type\":\"paragraph\",\"data\":{\"text\":\"Can the retrieved statement still be traced to an identifiable original source, or has it passed through summaries and copies whose origin is unclear?\"},\"tunes\":{}},{\"id\":\"254N_99Z7X\",\"type\":\"header\",\"data\":{\"text\":\"4. Applicability Distance\",\"level\":3},\"tunes\":{}},{\"id\":\"to3KWv5WSK\",\"type\":\"paragraph\",\"data\":{\"text\":\"How much reasoning is required to establish that the evidence applies to this exact version, user, jurisdiction, time period or situation?\"},\"tunes\":{}},{\"id\":\"3WnVPQ6wqw\",\"type\":\"header\",\"data\":{\"text\":\"Evidence Distance in RAG\",\"level\":2},\"tunes\":{}},{\"id\":\"r8s-75EBhA\",\"type\":\"paragraph\",\"data\":{\"text\":\"RAG can shorten one important distance: the distance between a model and external knowledge.\"},\"tunes\":{}},{\"id\":\"I_8h52A3Yc\",\"type\":\"paragraph\",\"data\":{\"text\":\"It does not automatically shorten the distance between a retrieved passage and the final claim.\"},\"tunes\":{}},{\"id\":\"jDDRUu2FUK\",\"type\":\"code\",\"data\":{\"code\":\"RAG solves:\\nmodel ↔ external information\\n\\nRAG does not automatically solve:\\nevidence ↔ justified conclusion\"},\"tunes\":{}},{\"id\":\"rm14qIVB1M\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhere-does-an-llm-get-its-data-rag-data-sources-in-python\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"Where Does an LLM Get Its Data? RAG Data Sources in Python\",\"description\":\"Retrieval brings external information into context. Evidence Distance asks what happens between that information and the claim eventually produced.\"}},\"tunes\":{}},{\"id\":\"CRUZDXYloa\",\"type\":\"header\",\"data\":{\"text\":\"Connection to the Retrieval Trigger\",\"level\":2},\"tunes\":{}},{\"id\":\"-TPiYJ569c\",\"type\":\"paragraph\",\"data\":{\"text\":\"The Retrieval Trigger asks whether internal model knowledge is sufficient.\"},\"tunes\":{}},{\"id\":\"_VjLi5fs4x\",\"type\":\"paragraph\",\"data\":{\"text\":\"Evidence Distance asks a later question: after evidence has been retrieved, how directly does it support what the system wants to claim?\"},\"tunes\":{}},{\"id\":\"EImPw6i617\",\"type\":\"code\",\"data\":{\"code\":\"Need evidence?\\n   ↓\\nRetrieval Trigger\\n   ↓\\nRetrieve\\n   ↓\\nHow directly does evidence support the claim?\\n   ↓\\nEvidence Distance\"},\"tunes\":{}},{\"id\":\"ZqyhB2bFtR\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhen-should-an-ai-stop-trusting-its-own-knowledge-the-retrieval-trigger\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"When Should an AI Stop Trusting Its Own Knowledge? — The Retrieval Trigger\",\"description\":\"The trigger decides when evidence is needed. Evidence Distance evaluates how far the eventual claim moves beyond that evidence.\"}},\"tunes\":{}},{\"id\":\"ST2vnm6vwF\",\"type\":\"header\",\"data\":{\"text\":\"A Practical Diagnostic\",\"level\":2},\"tunes\":{}},{\"id\":\"qyoHcDcTKb\",\"type\":\"paragraph\",\"data\":{\"text\":\"For an important AI-generated claim, reconstruct the support chain backwards.\"},\"tunes\":{}},{\"id\":\"e3fDmLk0fe\",\"type\":\"code\",\"data\":{\"code\":\"CLAIM\\n  ↑\\nWhich inference produced it?\\n  ↑\\nWhich retrieved evidence supports that inference?\\n  ↑\\nWhich source produced that evidence?\\n  ↑\\nCan the original source still be inspected?\"},\"tunes\":{}},{\"id\":\"iQ60c7NRaE\",\"type\":\"paragraph\",\"data\":{\"text\":\"If the chain breaks, the system has encountered an evidence-traceability problem.\"},\"tunes\":{}},{\"id\":\"YQAKlNZ2gM\",\"type\":\"paragraph\",\"data\":{\"text\":\"If the chain remains intact but requires several strong assumptions, the Evidence Distance is still high.\"},\"tunes\":{}},{\"id\":\"clN7jFkUBf\",\"type\":\"header\",\"data\":{\"text\":\"Example: Product Data\",\"level\":2},\"tunes\":{}},{\"id\":\"CRF-A9O7Ot\",\"type\":\"paragraph\",\"data\":{\"text\":\"Suppose a manufacturer specification says a laptop weighs 1.48 kg.\"},\"tunes\":{}},{\"id\":\"JF3z6aF2q_\",\"type\":\"code\",\"data\":{\"code\":\"Manufacturer specification\\n→ 1.48 kg\\n→ \\\"The laptop weighs 1.48 kg\\\"\\n\\nLow Evidence Distance\"},\"tunes\":{}},{\"id\":\"vTMOOgkLPb\",\"type\":\"paragraph\",\"data\":{\"text\":\"Now consider:\"},\"tunes\":{}},{\"id\":\"Tuhfzor1yp\",\"type\":\"code\",\"data\":{\"code\":\"Manufacturer specification\\n→ 1.48 kg\\n→ comparison with three competitors\\n→ assumption about travel behavior\\n→ \\\"This is the best laptop for frequent travelers\\\"\\n\\nMuch higher Evidence Distance\"},\"tunes\":{}},{\"id\":\"JHFRGIgUJD\",\"type\":\"paragraph\",\"data\":{\"text\":\"The specification is real. The recommendation is still several reasoning steps away from it.\"},\"tunes\":{}},{\"id\":\"2lKERCrnW1\",\"type\":\"header\",\"data\":{\"text\":\"Example: Scientific Evidence\",\"level\":2},\"tunes\":{}},{\"id\":\"HA8DBYwUuK\",\"type\":\"paragraph\",\"data\":{\"text\":\"A paper may report an observed association. An AI answer can incorrectly compress that into a causal statement.\"},\"tunes\":{}},{\"id\":\"D9C2dVB7j_\",\"type\":\"code\",\"data\":{\"code\":\"Observed association\\n        ↓\\nInterpretation\\n        ↓\\nUnstated causal assumption\\n        ↓\\n\\\"X causes Y\\\"\"},\"tunes\":{}},{\"id\":\"CKNjK25pkL\",\"type\":\"paragraph\",\"data\":{\"text\":\"The problem is not that no evidence exists. The problem is that the final statement crosses a larger evidential distance than the study directly supports.\"},\"tunes\":{}},{\"id\":\"sR430N3cDd\",\"type\":\"header\",\"data\":{\"text\":\"Connection to Agent-Ready Context\",\"level\":2},\"tunes\":{}},{\"id\":\"v77YyG55ko\",\"type\":\"paragraph\",\"data\":{\"text\":\"Structured information objects can reduce avoidable Evidence Distance by preserving source identity, units, timestamps, conflicts and validity instead of forcing the model to reconstruct them from flattened text.\"},\"tunes\":{}},{\"id\":\"EX8darCIjd\",\"type\":\"linkTool\",\"data\":{\"link\":\"https:\u002F\u002Fstajic.de\u002Fportfolio\u002Ffrom-raw-data-to-verifiable-ai-context-a-practical-architecture-for-agent-ready-information\",\"meta\":{\"image\":{\"url\":\"\"},\"title\":\"From Raw Data to Verifiable AI Context: A Practical Architecture for Agent-Ready Information\",\"description\":\"Preserving provenance and validity before retrieval reduces the number of unsupported reconstruction steps required later.\"}},\"tunes\":{}},{\"id\":\"dsfuoURj1e\",\"type\":\"header\",\"data\":{\"text\":\"A Simple Working Scale\",\"level\":2},\"tunes\":{}},{\"id\":\"BLi7Yth64O\",\"type\":\"table\",\"data\":{\"withHeadings\":true,\"stretched\":false,\"content\":[[\"Level\",\"Description\"],[\"ED0\",\"Directly reported source fact\"],[\"ED1\",\"Simple deterministic transformation or direct comparison\"],[\"ED2\",\"One meaningful interpretive step\"],[\"ED3\",\"Multiple assumptions or combined sources\"],[\"ED4\",\"Strong causal, predictive or prescriptive conclusion beyond direct evidence\"]]},\"tunes\":{}},{\"id\":\"8y8bzCcHBs\",\"type\":\"paragraph\",\"data\":{\"text\":\"This scale is illustrative, not a scientific standard. Its purpose is to force an explicit question: How much did we have to add between the evidence and the claim?\"},\"tunes\":{}},{\"id\":\"aFK0YiAlYO\",\"type\":\"header\",\"data\":{\"text\":\"Misconceptions\",\"level\":2},\"tunes\":{}},{\"id\":\"07KSk6xDx-\",\"type\":\"paragraph\",\"data\":{\"text\":\"A citation means Evidence Distance is low. No. A citation can sit beside a claim that substantially exceeds what the cited source establishes.\"},\"tunes\":{}},{\"id\":\"t_cf-Zfan9\",\"type\":\"paragraph\",\"data\":{\"text\":\"Long Evidence Distance means the claim is wrong. No. Complex conclusions can be well supported, but they require a stronger reasoning chain.\"},\"tunes\":{}},{\"id\":\"Pu9PRX67Q6\",\"type\":\"paragraph\",\"data\":{\"text\":\"Primary sources eliminate inference. No. Primary evidence can still require interpretation.\"},\"tunes\":{}},{\"id\":\"oF1xNsOHHq\",\"type\":\"paragraph\",\"data\":{\"text\":\"More sources automatically reduce distance. Ten weak repetitions of the same unsupported claim do not create direct evidence.\"},\"tunes\":{}},{\"id\":\"IkolK5baph\",\"type\":\"header\",\"data\":{\"text\":\"Edge Case: Derived Data\",\"level\":2},\"tunes\":{}},{\"id\":\"jRH36fwdR3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Some derived values are more reliable than raw human descriptions. A correctly calculated total from verified transactions can be highly dependable even though it is one transformation away from the original records.\"},\"tunes\":{}},{\"id\":\"SXbdKiNDst\",\"type\":\"paragraph\",\"data\":{\"text\":\"Evidence Distance therefore measures epistemic separation, not a simplistic preference for untouched data.\"},\"tunes\":{}},{\"id\":\"mUbvdnFChM\",\"type\":\"header\",\"data\":{\"text\":\"Limitations\",\"level\":2},\"tunes\":{}},{\"id\":\"N_EskxFOep\",\"type\":\"paragraph\",\"data\":{\"text\":\"Evidence Distance is a conceptual diagnostic, not a universal quantitative score.\"},\"tunes\":{}},{\"id\":\"nW_-E08So_\",\"type\":\"paragraph\",\"data\":{\"text\":\"Different domains require different treatment of inference. Mathematical proof, clinical evidence, software logs, market analysis and historical interpretation cannot share one universal numerical threshold.\"},\"tunes\":{}},{\"id\":\"_Bd95wXkri\",\"type\":\"header\",\"data\":{\"text\":\"What Would Change This Answer?\",\"level\":2},\"tunes\":{}},{\"id\":\"OqCaMc2_OX\",\"type\":\"paragraph\",\"data\":{\"text\":\"Future AI systems may generate explicit provenance graphs, machine-checkable claim-evidence links and typed reasoning traces. That could make parts of Evidence Distance measurable automatically.\"},\"tunes\":{}},{\"id\":\"58Hf3O9-Iz\",\"type\":\"paragraph\",\"data\":{\"text\":\"The underlying problem remains: a claim can move farther from its evidence even while every intermediate sentence sounds plausible.\"},\"tunes\":{}},{\"id\":\"8WOq5oE_e_\",\"type\":\"header\",\"data\":{\"text\":\"Conclusion\",\"level\":2},\"tunes\":{}},{\"id\":\"1pr1TfwnKc\",\"type\":\"paragraph\",\"data\":{\"text\":\"The important distinction is not merely between sourced and unsourced answers.\"},\"tunes\":{}},{\"id\":\"54CysT_NXa\",\"type\":\"paragraph\",\"data\":{\"text\":\"It is between claims that remain close to directly inspectable evidence and claims that depend on increasingly long chains of interpretation and assumption.\"},\"tunes\":{}},{\"id\":\"Qrjo3WEUSL\",\"type\":\"code\",\"data\":{\"code\":\"Evidence\\n   ↓\\nEvidence Distance\\n   ↓\\nReasoning\\n   ↓\\nAnswer Validity Boundary\"},\"tunes\":{}},{\"id\":\"6ir8aIAfd3\",\"type\":\"paragraph\",\"data\":{\"text\":\"Evidence Distance gives us a language for describing that space.\"},\"tunes\":{}},{\"id\":\"vPhupXcbeN\",\"type\":\"header\",\"data\":{\"text\":\"Primary Sources\",\"level\":2},\"tunes\":{}},{\"id\":\"BaO4JmWRQL\",\"type\":\"paragraph\",\"data\":{\"text\":\"Patrick Lewis et al., \u003Ca href=\\\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2005.11401\\\" target=\\\"_blank\\\">Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks\u003C\u002Fa> (2020).\"},\"tunes\":{}},{\"id\":\"eg4Z4G6Cgs\",\"type\":\"paragraph\",\"data\":{\"text\":\"Nelson F. Liu et al., \u003Ca href=\\\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.03172\\\" target=\\\"_blank\\\">Lost in the Middle: How Language Models Use Long Contexts\u003C\u002Fa> (2023).\"},\"tunes\":{}},{\"id\":\"BJH7zUd4T8\",\"type\":\"paragraph\",\"data\":{\"text\":\"W3C, \u003Ca href=\\\"https:\u002F\u002Fwww.w3.org\u002FTR\u002Fprov-overview\u002F\\\" target=\\\"_blank\\\">PROV Overview\u003C\u002Fa>. A standardized model for representing provenance relationships.\"},\"tunes\":{}}],\"version\":\"2.31.6\"}",{"time":776,"blocks":777,"version":740},1792096795538,[778,783,788,793,799,803,808,813,818,822,827,832,837,858,863,867,872,877,882,887,892,897,901,906,911,916,921,930,935,940,945,950,955,960,965,970,975,980,985,990,994,1003,1008,1013,1018,1022,1031,1036,1041,1045,1050,1055,1060,1065,1069,1074,1078,1083,1088,1093,1097,1102,1107,1112,1121,1126,1144,1149,1154,1159,1164,1169,1174,1179,1184,1189,1194,1199,1204,1209,1214,1219,1224,1229,1234,1238,1243,1248,1252,1256],{"id":779,"data":780,"type":42,"tunes":782},"g-2Ciyj8LJ",{"text":781,"level":234},"Question",{},{"id":784,"data":785,"type":240,"tunes":787},"SQWD7UraiX",{"text":786},"Two AI answers can both cite sources and still differ greatly in how directly those sources support the claims being made. How can we describe that difference?",{},{"id":789,"data":790,"type":240,"tunes":792},"Sj1fx2865j",{"text":791},"This article uses the term Evidence Distance for the distance between a claim and the directly inspectable evidence that supports it.",{},{"id":794,"data":795,"type":253,"tunes":798},"d5th-A-mq5",{"text":796,"caption":797,"alignment":252},"Evidence Distance is the number and strength of transformations, assumptions and inferential steps separating a claim from the evidence that can directly verify it.","Working definition — a reasoning concept introduced here, not a standardized metric.",{},{"id":800,"data":801,"type":260,"tunes":802},"X81jXC72FC",{"title":258,"maxLevel":259,"minLevel":234},{},{"id":804,"data":805,"type":42,"tunes":807},"_pZcnPEoil",{"text":806,"level":234},"What This Really Means",{},{"id":809,"data":810,"type":240,"tunes":812},"F5odO7xyha",{"text":811},"A citation proves that a source was referenced. It does not automatically prove that the source directly supports the sentence beside the citation.",{},{"id":814,"data":815,"type":240,"tunes":817},"8Gqlg-ArJS",{"text":816},"Between an original observation and a final AI answer there may be extraction, parsing, chunking, retrieval, summarization, interpretation, aggregation and inference.",{},{"id":819,"data":820,"type":281,"tunes":821},"lXkL5LV9ab",{"code":280},{},{"id":823,"data":824,"type":240,"tunes":826},"Z-8GPQIpCI",{"text":825},"Every step can be legitimate. But every step can also introduce distortion.",{},{"id":828,"data":829,"type":42,"tunes":831},"aXMwTGZ8Ia",{"text":830,"level":234},"Simplest Example",{},{"id":833,"data":834,"type":240,"tunes":836},"bZlU7KD3M2",{"text":835},"Suppose a temperature sensor reports 38.2 °C.",{},{"id":838,"data":839,"type":318,"tunes":857},"SP87UUPaU3",{"content":840,"stretched":43,"withHeadings":14},[841,845,849,853],[842,843,844],"Claim","Relationship to evidence","Illustrative distance",[846,847,848],"The sensor reports 38.2 °C.","Direct reading","Low",[850,851,852],"The system is running hotter than yesterday.","Requires comparison with yesterday's reading","Moderate",[854,855,856],"The cooling system is failing.","Requires causal inference and alternative explanations","High",{},{"id":859,"data":860,"type":240,"tunes":862},"eYar059d69",{"text":861},"The original sensor value directly supports the first claim. It does not by itself prove the third.",{},{"id":864,"data":865,"type":281,"tunes":866},"eCnFlByvHt",{"code":328},{},{"id":868,"data":869,"type":42,"tunes":871},"aXGkK6BpkF",{"text":870,"level":234},"Where the Example Stops Working",{},{"id":873,"data":874,"type":240,"tunes":876},"lAwb9QZ_yB",{"text":875},"Evidence Distance is not simply a count of sentences or processing steps.",{},{"id":878,"data":879,"type":240,"tunes":881},"-SzYko9oIH",{"text":880},"One mathematically valid transformation may preserve evidence almost perfectly, while a single speculative interpretation may create a much larger epistemic jump.",{},{"id":883,"data":884,"type":240,"tunes":886},"XOQloBndLw",{"text":885},"The concept therefore includes both distance by transformation and distance by inference.",{},{"id":888,"data":889,"type":42,"tunes":891},"EOXbS4TAOR",{"text":890,"level":234},"Direct Answer",{},{"id":893,"data":894,"type":240,"tunes":896},"HcVL8vGM74",{"text":895},"Evidence Distance increases when a claim depends on more transformations, more assumptions, weaker provenance or stronger inference than the underlying evidence directly warrants.",{},{"id":898,"data":899,"type":281,"tunes":900},"_f7WXjUOsS",{"code":363},{},{"id":902,"data":903,"type":240,"tunes":905},"zUEC-cDhqm",{"text":904},"A longer distance does not automatically make a claim false. It means the reasoning chain requires more validation.",{},{"id":907,"data":908,"type":42,"tunes":910},"ix7TUGNz_W",{"text":909,"level":234},"Why This Matters for AI",{},{"id":912,"data":913,"type":240,"tunes":915},"wrAy5PLtLB",{"text":914},"LLMs are particularly good at producing fluent bridges between pieces of information. That capability is useful, but fluency can hide how far the conclusion has moved beyond the directly retrieved evidence.",{},{"id":917,"data":918,"type":240,"tunes":920},"jJseLuTWdv",{"text":919},"An answer can therefore look well sourced while containing claims whose support exists only through several unstated inferential steps.",{},{"id":922,"data":923,"type":394,"tunes":929},"ox8fok9dzs",{"link":924,"meta":925},"https:\u002F\u002Fstajic.de\u002Fblog\u002Ffrom-research-protocol-to-a-general-ai-reasoning-framework",{"image":926,"title":927,"description":928},{"url":391},"From Research Protocol to a General AI Reasoning Framework","Reliable reasoning requires explicit separation of evidence, assumptions, hypotheses and conclusions.",{},{"id":931,"data":932,"type":42,"tunes":934},"6ipse6YG1U",{"text":933,"level":234},"Four Components of Evidence Distance",{},{"id":936,"data":937,"type":42,"tunes":939},"P4xQ7o96dR",{"text":938,"level":259},"1. Transformation Distance",{},{"id":941,"data":942,"type":240,"tunes":944},"dvN8TUNEYG",{"text":943},"How many times has the original evidence been converted, summarized, normalized or reformatted before reaching the model?",{},{"id":946,"data":947,"type":42,"tunes":949},"dXofACF9_x",{"text":948,"level":259},"2. Inferential Distance",{},{"id":951,"data":952,"type":240,"tunes":954},"kkEzV3ydId",{"text":953},"How many reasoning steps are required before the evidence supports the final conclusion?",{},{"id":956,"data":957,"type":42,"tunes":959},"PPYB0RuX5_",{"text":958,"level":259},"3. Provenance Distance",{},{"id":961,"data":962,"type":240,"tunes":964},"cAVBYebJr7",{"text":963},"Can the retrieved statement still be traced to an identifiable original source, or has it passed through summaries and copies whose origin is unclear?",{},{"id":966,"data":967,"type":42,"tunes":969},"254N_99Z7X",{"text":968,"level":259},"4. Applicability Distance",{},{"id":971,"data":972,"type":240,"tunes":974},"to3KWv5WSK",{"text":973},"How much reasoning is required to establish that the evidence applies to this exact version, user, jurisdiction, time period or situation?",{},{"id":976,"data":977,"type":42,"tunes":979},"3WnVPQ6wqw",{"text":978,"level":234},"Evidence Distance in RAG",{},{"id":981,"data":982,"type":240,"tunes":984},"r8s-75EBhA",{"text":983},"RAG can shorten one important distance: the distance between a model and external knowledge.",{},{"id":986,"data":987,"type":240,"tunes":989},"I_8h52A3Yc",{"text":988},"It does not automatically shorten the distance between a retrieved passage and the final claim.",{},{"id":991,"data":992,"type":281,"tunes":993},"jDDRUu2FUK",{"code":459},{},{"id":995,"data":996,"type":394,"tunes":1002},"rm14qIVB1M",{"link":997,"meta":998},"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhere-does-an-llm-get-its-data-rag-data-sources-in-python",{"image":999,"title":1000,"description":1001},{"url":391},"Where Does an LLM Get Its Data? RAG Data Sources in Python","Retrieval brings external information into context. Evidence Distance asks what happens between that information and the claim eventually produced.",{},{"id":1004,"data":1005,"type":42,"tunes":1007},"CRUZDXYloa",{"text":1006,"level":234},"Connection to the Retrieval Trigger",{},{"id":1009,"data":1010,"type":240,"tunes":1012},"-TPiYJ569c",{"text":1011},"The Retrieval Trigger asks whether internal model knowledge is sufficient.",{},{"id":1014,"data":1015,"type":240,"tunes":1017},"_VjLi5fs4x",{"text":1016},"Evidence Distance asks a later question: after evidence has been retrieved, how directly does it support what the system wants to claim?",{},{"id":1019,"data":1020,"type":281,"tunes":1021},"EImPw6i617",{"code":488},{},{"id":1023,"data":1024,"type":394,"tunes":1030},"ZqyhB2bFtR",{"link":1025,"meta":1026},"https:\u002F\u002Fstajic.de\u002Fblog\u002Fwhen-should-an-ai-stop-trusting-its-own-knowledge-the-retrieval-trigger",{"image":1027,"title":1028,"description":1029},{"url":391},"When Should an AI Stop Trusting Its Own Knowledge? — The Retrieval Trigger","The trigger decides when evidence is needed. Evidence Distance evaluates how far the eventual claim moves beyond that evidence.",{},{"id":1032,"data":1033,"type":42,"tunes":1035},"ST2vnm6vwF",{"text":1034,"level":234},"A Practical Diagnostic",{},{"id":1037,"data":1038,"type":240,"tunes":1040},"qyoHcDcTKb",{"text":1039},"For an important AI-generated claim, reconstruct the support chain backwards.",{},{"id":1042,"data":1043,"type":281,"tunes":1044},"e3fDmLk0fe",{"code":512},{},{"id":1046,"data":1047,"type":240,"tunes":1049},"iQ60c7NRaE",{"text":1048},"If the chain breaks, the system has encountered an evidence-traceability problem.",{},{"id":1051,"data":1052,"type":240,"tunes":1054},"YQAKlNZ2gM",{"text":1053},"If the chain remains intact but requires several strong assumptions, the Evidence Distance is still high.",{},{"id":1056,"data":1057,"type":42,"tunes":1059},"clN7jFkUBf",{"text":1058,"level":234},"Example: Product Data",{},{"id":1061,"data":1062,"type":240,"tunes":1064},"CRF-A9O7Ot",{"text":1063},"Suppose a manufacturer specification says a laptop weighs 1.48 kg.",{},{"id":1066,"data":1067,"type":281,"tunes":1068},"JF3z6aF2q_",{"code":537},{},{"id":1070,"data":1071,"type":240,"tunes":1073},"vTMOOgkLPb",{"text":1072},"Now consider:",{},{"id":1075,"data":1076,"type":281,"tunes":1077},"Tuhfzor1yp",{"code":547},{},{"id":1079,"data":1080,"type":240,"tunes":1082},"JHFRGIgUJD",{"text":1081},"The specification is real. The recommendation is still several reasoning steps away from it.",{},{"id":1084,"data":1085,"type":42,"tunes":1087},"2lKERCrnW1",{"text":1086,"level":234},"Example: Scientific Evidence",{},{"id":1089,"data":1090,"type":240,"tunes":1092},"HA8DBYwUuK",{"text":1091},"A paper may report an observed association. An AI answer can incorrectly compress that into a causal statement.",{},{"id":1094,"data":1095,"type":281,"tunes":1096},"D9C2dVB7j_",{"code":567},{},{"id":1098,"data":1099,"type":240,"tunes":1101},"CKNjK25pkL",{"text":1100},"The problem is not that no evidence exists. The problem is that the final statement crosses a larger evidential distance than the study directly supports.",{},{"id":1103,"data":1104,"type":42,"tunes":1106},"sR430N3cDd",{"text":1105,"level":234},"Connection to Agent-Ready Context",{},{"id":1108,"data":1109,"type":240,"tunes":1111},"v77YyG55ko",{"text":1110},"Structured information objects can reduce avoidable Evidence Distance by preserving source identity, units, timestamps, conflicts and validity instead of forcing the model to reconstruct them from flattened text.",{},{"id":1113,"data":1114,"type":394,"tunes":1120},"EX8darCIjd",{"link":1115,"meta":1116},"https:\u002F\u002Fstajic.de\u002Fportfolio\u002Ffrom-raw-data-to-verifiable-ai-context-a-practical-architecture-for-agent-ready-information",{"image":1117,"title":1118,"description":1119},{"url":391},"From Raw Data to Verifiable AI Context: A Practical Architecture for Agent-Ready Information","Preserving provenance and validity before retrieval reduces the number of unsupported reconstruction steps required later.",{},{"id":1122,"data":1123,"type":42,"tunes":1125},"dsfuoURj1e",{"text":1124,"level":234},"A Simple Working Scale",{},{"id":1127,"data":1128,"type":318,"tunes":1143},"BLi7Yth64O",{"content":1129,"stretched":43,"withHeadings":14},[1130,1133,1135,1137,1139,1141],[1131,1132],"Level","Description",[605,1134],"Directly reported source fact",[608,1136],"Simple deterministic transformation or direct comparison",[611,1138],"One meaningful interpretive step",[614,1140],"Multiple assumptions or combined sources",[617,1142],"Strong causal, predictive or prescriptive conclusion beyond direct evidence",{},{"id":1145,"data":1146,"type":240,"tunes":1148},"8y8bzCcHBs",{"text":1147},"This scale is illustrative, not a scientific standard. Its purpose is to force an explicit question: How much did we have to add between the evidence and the claim?",{},{"id":1150,"data":1151,"type":42,"tunes":1153},"aFK0YiAlYO",{"text":1152,"level":234},"Misconceptions",{},{"id":1155,"data":1156,"type":240,"tunes":1158},"07KSk6xDx-",{"text":1157},"A citation means Evidence Distance is low. No. A citation can sit beside a claim that substantially exceeds what the cited source establishes.",{},{"id":1160,"data":1161,"type":240,"tunes":1163},"t_cf-Zfan9",{"text":1162},"Long Evidence Distance means the claim is wrong. No. Complex conclusions can be well supported, but they require a stronger reasoning chain.",{},{"id":1165,"data":1166,"type":240,"tunes":1168},"Pu9PRX67Q6",{"text":1167},"Primary sources eliminate inference. No. Primary evidence can still require interpretation.",{},{"id":1170,"data":1171,"type":240,"tunes":1173},"oF1xNsOHHq",{"text":1172},"More sources automatically reduce distance. Ten weak repetitions of the same unsupported claim do not create direct evidence.",{},{"id":1175,"data":1176,"type":42,"tunes":1178},"IkolK5baph",{"text":1177,"level":234},"Edge Case: Derived Data",{},{"id":1180,"data":1181,"type":240,"tunes":1183},"jRH36fwdR3",{"text":1182},"Some derived values are more reliable than raw human descriptions. A correctly calculated total from verified transactions can be highly dependable even though it is one transformation away from the original records.",{},{"id":1185,"data":1186,"type":240,"tunes":1188},"SXbdKiNDst",{"text":1187},"Evidence Distance therefore measures epistemic separation, not a simplistic preference for untouched data.",{},{"id":1190,"data":1191,"type":42,"tunes":1193},"mUbvdnFChM",{"text":1192,"level":234},"Limitations",{},{"id":1195,"data":1196,"type":240,"tunes":1198},"N_EskxFOep",{"text":1197},"Evidence Distance is a conceptual diagnostic, not a universal quantitative score.",{},{"id":1200,"data":1201,"type":240,"tunes":1203},"nW_-E08So_",{"text":1202},"Different domains require different treatment of inference. Mathematical proof, clinical evidence, software logs, market analysis and historical interpretation cannot share one universal numerical threshold.",{},{"id":1205,"data":1206,"type":42,"tunes":1208},"_Bd95wXkri",{"text":1207,"level":234},"What Would Change This Answer?",{},{"id":1210,"data":1211,"type":240,"tunes":1213},"OqCaMc2_OX",{"text":1212},"Future AI systems may generate explicit provenance graphs, machine-checkable claim-evidence links and typed reasoning traces. That could make parts of Evidence Distance measurable automatically.",{},{"id":1215,"data":1216,"type":240,"tunes":1218},"58Hf3O9-Iz",{"text":1217},"The underlying problem remains: a claim can move farther from its evidence even while every intermediate sentence sounds plausible.",{},{"id":1220,"data":1221,"type":42,"tunes":1223},"8WOq5oE_e_",{"text":1222,"level":234},"Conclusion",{},{"id":1225,"data":1226,"type":240,"tunes":1228},"1pr1TfwnKc",{"text":1227},"The important distinction is not merely between sourced and unsourced answers.",{},{"id":1230,"data":1231,"type":240,"tunes":1233},"54CysT_NXa",{"text":1232},"It is between claims that remain close to directly inspectable evidence and claims that depend on increasingly long chains of interpretation and assumption.",{},{"id":1235,"data":1236,"type":281,"tunes":1237},"Qrjo3WEUSL",{"code":713},{},{"id":1239,"data":1240,"type":240,"tunes":1242},"6ir8aIAfd3",{"text":1241},"Evidence Distance gives us a language for describing that space.",{},{"id":1244,"data":1245,"type":42,"tunes":1247},"vPhupXcbeN",{"text":1246,"level":234},"Primary Sources",{},{"id":1249,"data":1250,"type":240,"tunes":1251},"BaO4JmWRQL",{"text":728},{},{"id":1253,"data":1254,"type":240,"tunes":1255},"eg4Z4G6Cgs",{"text":733},{},{"id":1257,"data":1258,"type":240,"tunes":1260},"BJH7zUd4T8",{"text":1259},"W3C, \u003Ca href=\"https:\u002F\u002Fwww.w3.org\u002FTR\u002Fprov-overview\u002F\" target=\"_blank\">PROV Overview\u003C\u002Fa>. A standardized model for representing provenance relationships.",{},"Not all supported answers are equally close to their evidence. Evidence Distance is a practical way to describe how many transformations, summaries, assumptions and inferential steps separate an AI claim from directly inspectable evidence.",{"lang":7,"title":224,"content":226,"contentJson":1263,"excerpt":741},{"time":228,"blocks":1264,"version":740},[1265,1268,1271,1274,1277,1280,1283,1286,1289,1292,1295,1298,1301,1309,1312,1315,1318,1321,1324,1327,1330,1333,1336,1339,1342,1345,1348,1353,1356,1359,1362,1365,1368,1371,1374,1377,1380,1383,1386,1389,1392,1397,1400,1403,1406,1409,1414,1417,1420,1423,1426,1429,1432,1435,1438,1441,1444,1447,1450,1453,1456,1459,1462,1465,1470,1473,1483,1486,1489,1492,1495,1498,1501,1504,1507,1510,1513,1516,1519,1522,1525,1528,1531,1534,1537,1540,1543,1546,1549,1552],{"id":231,"data":1266,"type":42,"tunes":1267},{"text":233,"level":234},{},{"id":237,"data":1269,"type":240,"tunes":1270},{"text":239},{},{"id":243,"data":1272,"type":240,"tunes":1273},{"text":245},{},{"id":248,"data":1275,"type":253,"tunes":1276},{"text":250,"caption":251,"alignment":252},{},{"id":256,"data":1278,"type":260,"tunes":1279},{"title":258,"maxLevel":259,"minLevel":234},{},{"id":263,"data":1281,"type":42,"tunes":1282},{"text":265,"level":234},{},{"id":268,"data":1284,"type":240,"tunes":1285},{"text":270},{},{"id":273,"data":1287,"type":240,"tunes":1288},{"text":275},{},{"id":278,"data":1290,"type":281,"tunes":1291},{"code":280},{},{"id":284,"data":1293,"type":240,"tunes":1294},{"text":286},{},{"id":289,"data":1296,"type":42,"tunes":1297},{"text":291,"level":234},{},{"id":294,"data":1299,"type":240,"tunes":1300},{"text":296},{},{"id":299,"data":1302,"type":318,"tunes":1308},{"content":1303,"stretched":43,"withHeadings":14},[1304,1305,1306,1307],[303,304,305],[307,308,309],[311,312,313],[315,316,317],{},{"id":321,"data":1310,"type":240,"tunes":1311},{"text":323},{},{"id":326,"data":1313,"type":281,"tunes":1314},{"code":328},{},{"id":331,"data":1316,"type":42,"tunes":1317},{"text":333,"level":234},{},{"id":336,"data":1319,"type":240,"tunes":1320},{"text":338},{},{"id":341,"data":1322,"type":240,"tunes":1323},{"text":343},{},{"id":346,"data":1325,"type":240,"tunes":1326},{"text":348},{},{"id":351,"data":1328,"type":42,"tunes":1329},{"text":353,"level":234},{},{"id":356,"data":1331,"type":240,"tunes":1332},{"text":358},{},{"id":361,"data":1334,"type":281,"tunes":1335},{"code":363},{},{"id":366,"data":1337,"type":240,"tunes":1338},{"text":368},{},{"id":371,"data":1340,"type":42,"tunes":1341},{"text":373,"level":234},{},{"id":376,"data":1343,"type":240,"tunes":1344},{"text":378},{},{"id":381,"data":1346,"type":240,"tunes":1347},{"text":383},{},{"id":386,"data":1349,"type":394,"tunes":1352},{"link":388,"meta":1350},{"image":1351,"title":392,"description":393},{"url":391},{},{"id":397,"data":1354,"type":42,"tunes":1355},{"text":399,"level":234},{},{"id":402,"data":1357,"type":42,"tunes":1358},{"text":404,"level":259},{},{"id":407,"data":1360,"type":240,"tunes":1361},{"text":409},{},{"id":412,"data":1363,"type":42,"tunes":1364},{"text":414,"level":259},{},{"id":417,"data":1366,"type":240,"tunes":1367},{"text":419},{},{"id":422,"data":1369,"type":42,"tunes":1370},{"text":424,"level":259},{},{"id":427,"data":1372,"type":240,"tunes":1373},{"text":429},{},{"id":432,"data":1375,"type":42,"tunes":1376},{"text":434,"level":259},{},{"id":437,"data":1378,"type":240,"tunes":1379},{"text":439},{},{"id":442,"data":1381,"type":42,"tunes":1382},{"text":444,"level":234},{},{"id":447,"data":1384,"type":240,"tunes":1385},{"text":449},{},{"id":452,"data":1387,"type":240,"tunes":1388},{"text":454},{},{"id":457,"data":1390,"type":281,"tunes":1391},{"code":459},{},{"id":462,"data":1393,"type":394,"tunes":1396},{"link":464,"meta":1394},{"image":1395,"title":467,"description":468},{"url":391},{},{"id":471,"data":1398,"type":42,"tunes":1399},{"text":473,"level":234},{},{"id":476,"data":1401,"type":240,"tunes":1402},{"text":478},{},{"id":481,"data":1404,"type":240,"tunes":1405},{"text":483},{},{"id":486,"data":1407,"type":281,"tunes":1408},{"code":488},{},{"id":491,"data":1410,"type":394,"tunes":1413},{"link":493,"meta":1411},{"image":1412,"title":496,"description":497},{"url":391},{},{"id":500,"data":1415,"type":42,"tunes":1416},{"text":502,"level":234},{},{"id":505,"data":1418,"type":240,"tunes":1419},{"text":507},{},{"id":510,"data":1421,"type":281,"tunes":1422},{"code":512},{},{"id":515,"data":1424,"type":240,"tunes":1425},{"text":517},{},{"id":520,"data":1427,"type":240,"tunes":1428},{"text":522},{},{"id":525,"data":1430,"type":42,"tunes":1431},{"text":527,"level":234},{},{"id":530,"data":1433,"type":240,"tunes":1434},{"text":532},{},{"id":535,"data":1436,"type":281,"tunes":1437},{"code":537},{},{"id":540,"data":1439,"type":240,"tunes":1440},{"text":542},{},{"id":545,"data":1442,"type":281,"tunes":1443},{"code":547},{},{"id":550,"data":1445,"type":240,"tunes":1446},{"text":552},{},{"id":555,"data":1448,"type":42,"tunes":1449},{"text":557,"level":234},{},{"id":560,"data":1451,"type":240,"tunes":1452},{"text":562},{},{"id":565,"data":1454,"type":281,"tunes":1455},{"code":567},{},{"id":570,"data":1457,"type":240,"tunes":1458},{"text":572},{},{"id":575,"data":1460,"t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