{"id":"https://openalex.org/W7163676635","doi":"https://doi.org/10.48550/arxiv.2606.05206","title":"Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature","display_name":"Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature","publication_year":2026,"publication_date":"2026-05-23","ids":{"openalex":"https://openalex.org/W7163676635","doi":"https://doi.org/10.48550/arxiv.2606.05206"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.05206","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05206","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.05206","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094283439","display_name":"Hamed Nejat","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nejat, Hamed","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040252856","display_name":"Alexander Maier","orcid":"https://orcid.org/0000-0002-7250-502X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maier, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137665335","display_name":"Jesse Spencer-Smith","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Spencer-Smith, Jesse","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137688306","display_name":"Andr\u00e9 M. Bastos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bastos, Andr\u00e9 M.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.28929999470710754,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.28929999470710754,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.125900000333786,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10465","display_name":"Neurobiology of Language and Bilingualism","score":0.0658000037074089,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/glossary","display_name":"Glossary","score":0.6480000019073486},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5697000026702881},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5006999969482422},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.48399999737739563},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.46880000829696655},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.38440001010894775}],"concepts":[{"id":"https://openalex.org/C2780031656","wikidata":"https://www.wikidata.org/wiki/Q859161","display_name":"Glossary","level":2,"score":0.6480000019073486},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5697000026702881},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5627999901771545},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5347999930381775},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5006999969482422},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.48399999737739563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48080000281333923},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.46880000829696655},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C22334291","wikidata":"https://www.wikidata.org/wiki/Q7077468","display_name":"Oddball paradigm","level":4,"score":0.37619999051094055},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3190000057220459},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2766999900341034},{"id":"https://openalex.org/C2778589607","wikidata":"https://www.wikidata.org/wiki/Q1250335","display_name":"Animacy","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2606000006198883},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.05206","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05206","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.05206","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.05206","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Fragmentation":[0],"is":[1,15],"common":[2,229],"in":[3,179],"interdisciplinary":[4],"fields":[5],"with":[6,105],"diverse":[7],"methods":[8],"and":[9,27,62,87,111,122,170],"theoretical":[10],"commitments.":[11],"Predictive":[12],"coding":[13],"neuroscience":[14],"a":[16,30,42,72,151,228],"clear":[17],"example:":[18],"its":[19],"literature":[20,48],"spans":[21],"computational":[22],"theory,":[23],"electrophysiology,":[24],"imaging,":[25],"behavior,":[26],"modeling,":[28],"creating":[29],"synthesis":[31],"problem":[32],"that":[33,199,208],"conventional":[34,225],"meta-analysis":[35,226],"cannot":[36],"easily":[37],"resolve.":[38],"Here,":[39],"we":[40],"describe":[41],"local":[43,93,110,141,167,200],"multi-LLM":[44,201],"pipeline":[45,51],"for":[46,129,134,166,172],"ontology-constrained":[47],"synthesis.":[49],"The":[50,182],"reads":[52],"papers,":[53],"extracts":[54],"evidence,":[55],"incorporates":[56],"figure":[57],"descriptions,":[58],"assembles":[59],"constrained":[60],"prompts,":[61],"validates":[63],"outputs":[64],"against":[65],"an":[66],"expert":[67],"glossary.":[68],"We":[69,146],"manually":[70],"defined":[71],"predictive-coding":[73],"glossary":[74,107],"of":[75,91,191],"thirty-six":[76],"concepts":[77],"grouped":[78],"into":[79,212],"three":[80],"hypotheses:":[81],"predictive":[82],"suppression,":[83],"feedforward":[84],"error":[85],"propagation,":[86],"ubiquity.":[88],"A":[89],"council":[90],"ten":[92],"language":[94],"models":[95],"scored":[96],"31":[97],"studies":[98,158],"according":[99],"to":[100,188,220],"their":[101],"agreement":[102],"or":[103],"disagreement":[104,206],"each":[106],"factor":[108],"across":[109,140],"global":[112,143,173],"oddball":[113,144,168,174],"contexts.":[114,195],"This":[115,216],"enabled":[116],"pairwise":[117],"study-agreement":[118],"analysis,":[119],"cross-model":[120],"comparison,":[121],"three-dimensional":[123],"hypothesis-space":[124,149],"mapping.":[125],"Agreement":[126],"was":[127,164],"high":[128],"some":[130],"hypotheses":[131],"but":[132],"weaker":[133],"others,":[135],"revealing":[136],"structured":[137],"disagreement,":[138],"particularly":[139],"versus":[142],"paradigms.":[145],"further":[147],"define":[148],"temperature,":[150],"geometric":[152],"dispersion":[153,178],"metric":[154],"measuring":[155],"how":[156],"compactly":[157],"occupy":[159],"the":[160,180],"hypothesis":[161,222],"space.":[162,231],"Temperature":[163],"lower":[165],"contexts":[169],"higher":[171],"contexts,":[175],"indicating":[176],"greater":[177],"latter.":[181],"scoring":[183],"geometry":[184],"also":[185],"allowed":[186],"us":[187],"estimate":[189],"vectors":[190],"change":[192],"between":[193],"experimental":[194],"These":[196],"results":[197],"demonstrate":[198],"councils":[202],"can":[203],"produce":[204],"auditable":[205],"measurements":[207],"map":[209],"heterogeneous":[210],"literatures":[211],"quantitative":[213],"evidence":[214],"spaces.":[215],"framework":[217],"may":[218],"generalize":[219],"cross-study":[221],"mapping":[223],"where":[224],"lacks":[227],"comparison":[230]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-06T00:00:00"}