{"id":"https://openalex.org/W7223878705","doi":"https://doi.org/10.1371/journal.pone.0361281","title":"On the variability of generative artificial intelligence methods in conceptual modeling: an experimental evaluation on combining causal maps","display_name":"On the variability of generative artificial intelligence methods in conceptual modeling: an experimental evaluation on combining causal maps","publication_year":2026,"publication_date":"2026-10-27","ids":{"openalex":"https://openalex.org/W7223878705","doi":"https://doi.org/10.1371/journal.pone.0361281","pmid":"https://pubmed.ncbi.nlm.nih.gov/42945229","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13712584"},"language":"en","primary_location":{"id":"doi:10.1371/journal.pone.0361281","doi":"https://doi.org/10.1371/journal.pone.0361281","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0361281","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0361281&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0361281&type=printable","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114403859","display_name":"No\u00e9 Yves Jean-Pierre Flandre","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210127738","display_name":"IMT Mines Al\u00e8s","ror":"https://ror.org/03e8rf594","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210127738"]},{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["FR","US"],"is_corresponding":false,"raw_author_name":"No\u00e9 Y. Flandre","raw_affiliation_strings":["Old Dominion University (ODU) Virginia Modeling, Analysis, and Simulation Center (VMASC)","School of Mines in Al\u00e8s (IMT Mines Al\u00e8s)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Old Dominion University (ODU) Virginia Modeling, Analysis, and Simulation Center (VMASC)","institution_ids":["https://openalex.org/I81365321"]},{"raw_affiliation_string":"School of Mines in Al\u00e8s (IMT Mines Al\u00e8s)","institution_ids":["https://openalex.org/I4210127738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114618673","display_name":"C. Daumas","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210127738","display_name":"IMT Mines Al\u00e8s","ror":"https://ror.org/03e8rf594","country_code":"FR","type":"education","lineage":["https://openalex.org/I205703379","https://openalex.org/I4210127738"]},{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["FR","US"],"is_corresponding":false,"raw_author_name":"C\u00e9dric Daumas","raw_affiliation_strings":["Old Dominion University (ODU) Virginia Modeling, Analysis, and Simulation Center (VMASC)","School of Mines in Al\u00e8s (IMT Mines Al\u00e8s)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Old Dominion University (ODU) Virginia Modeling, Analysis, and Simulation Center (VMASC)","institution_ids":["https://openalex.org/I81365321"]},{"raw_affiliation_string":"School of Mines in Al\u00e8s (IMT Mines Al\u00e8s)","institution_ids":["https://openalex.org/I4210127738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023496425","display_name":"Philippe J. Giabbanelli","orcid":"https://orcid.org/0000-0001-6816-355X","observed_orcids":["https://orcid.org/0000-0001-6816-355X"]},"institutions":[{"id":"https://openalex.org/I81365321","display_name":"Old Dominion University","ror":"https://ror.org/04zjtrb98","country_code":"US","type":"education","lineage":["https://openalex.org/I81365321"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Philippe J. Giabbanelli","raw_affiliation_strings":["Old Dominion University (ODU) Virginia Modeling, Analysis, and Simulation Center (VMASC)"],"raw_orcid":"https://orcid.org/0000-0001-6816-355X","affiliations":[{"raw_affiliation_string":"Old Dominion University (ODU) Virginia Modeling, Analysis, and Simulation Center (VMASC)","institution_ids":["https://openalex.org/I81365321"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5023496425"],"corresponding_institution_ids":["https://openalex.org/I81365321"],"apc_list":{"value":2382,"currency":"USD","value_usd":2382},"apc_paid":{"value":2382,"currency":"USD","value_usd":2382},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.80353734,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":"10","first_page":"e0361281","last_page":"e0361281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5327000021934509,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.5327000021934509,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.15760000050067902,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11810","display_name":"Complex Systems and Decision Making","score":0.040699999779462814,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.8949999809265137},{"id":"https://openalex.org/keywords/causal-maps","display_name":"causal maps","score":0.777999997138977},{"id":"https://openalex.org/keywords/conceptual-modeling","display_name":"conceptual modeling","score":0.9610000252723694},{"id":"https://openalex.org/keywords/model-combination","display_name":"model combination","score":0.722000002861023},{"id":"https://openalex.org/keywords/replicability","display_name":"replicability","score":0.7139999866485596},{"id":"https://openalex.org/keywords/decoding-strategies","display_name":"decoding strategies","score":0.8669999837875366},{"id":"https://openalex.org/keywords/beam-search","display_name":"beam search","score":0.7160000205039978},{"id":"https://openalex.org/keywords/greedy-decoding","display_name":"greedy decoding","score":0.8529999852180481},{"id":"https://openalex.org/keywords/contrastive-decoding","display_name":"contrastive decoding","score":0.9110000133514404},{"id":"https://openalex.org/keywords/prompt-effects","display_name":"prompt effects","score":0.7940000295639038},{"id":"https://openalex.org/keywords/factorial-design","display_name":"factorial design","score":0.43299999833106995},{"id":"https://openalex.org/keywords/generative-ai","display_name":"generative AI","score":0.5550000071525574}],"concepts":[{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.5564000010490417},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5450999736785889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5436000227928162},{"id":"https://openalex.org/C2779010991","wikidata":"https://www.wikidata.org/wiki/Q2720909","display_name":"Artifact (error)","level":2,"score":0.5317999720573425},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5055999755859375},{"id":"https://openalex.org/C11671645","wikidata":"https://www.wikidata.org/wiki/Q5054567","display_name":"Causal model","level":2,"score":0.49630001187324524},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48730000853538513},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.46160000562667847},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.41499999165534973},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.4077000021934509},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.4065000116825104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4043999910354614},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.3937000036239624},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.36660000681877136},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.3659999966621399},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.3490000069141388},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32100000977516174},{"id":"https://openalex.org/C197640229","wikidata":"https://www.wikidata.org/wiki/Q2534066","display_name":"Predictability","level":2,"score":0.3165000081062317},{"id":"https://openalex.org/C9114305","wikidata":"https://www.wikidata.org/wiki/Q1428317","display_name":"Situational ethics","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.2953999936580658},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2768999934196472},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27140000462532043},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C130440534","wikidata":"https://www.wikidata.org/wiki/Q14946528","display_name":"Conflation","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2500999867916107}],"mesh":[{"descriptor_ui":"D000098342","descriptor_name":"Large Language Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000098842","descriptor_name":"Generative Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.1371/journal.pone.0361281","doi":"https://doi.org/10.1371/journal.pone.0361281","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0361281","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0361281&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13712584","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13712584/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13712584/pdf/pone.0361281.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLoS One","raw_type":"Text"},{"id":"pmid:42945229","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42945229","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PloS one","raw_type":"Journal Article"},{"id":"pmh:oai:HAL:hal-05842285v1","doi":null,"is_oa":true,"landing_page_url":"https://imt-mines-ales.hal.science/hal-05842285","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4405252976","host_organization_name":"Centre pour la Communication Scientifique Directe","host_organization_lineage":["https://openalex.org/I4405252976"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS ONE, 2026, 21 (10), pp.e0361281. &#x27E8;10.1371/journal.pone.0361281&#x27E9;","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:6c17c32f9c014c0ab38f0adffbc15417","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/6c17c32f9c014c0ab38f0adffbc15417","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"PLoS ONE, Vol 21, Iss 10, p e0361281 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1371/journal.pone.0361281","doi":"https://doi.org/10.1371/journal.pone.0361281","is_oa":true,"landing_page_url":"https://doi.org/10.1371/journal.pone.0361281","pdf_url":"https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0361281&type=printable","source":{"id":"https://openalex.org/S202381698","display_name":"PLoS ONE","issn_l":"1932-6203","issn":["1932-6203"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","dongbi-c","doyens","erih-plus","jufo-1","ki-jl-1","medline","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310315706","host_organization_name":"Public Library of Science","host_organization_lineage":["https://openalex.org/P4310315706"],"host_organization_lineage_names":["Public Library of Science"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"PLOS One","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7223878705.pdf","grobid_xml":"https://content.openalex.org/works/W7223878705.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W2047029075","https://openalex.org/W2090027043","https://openalex.org/W2106368352","https://openalex.org/W2114962442","https://openalex.org/W2744736274","https://openalex.org/W2760371526","https://openalex.org/W2889262254","https://openalex.org/W2906205635","https://openalex.org/W3123800493","https://openalex.org/W3202406170","https://openalex.org/W3207160649","https://openalex.org/W4211076749","https://openalex.org/W4238601124","https://openalex.org/W4253887561","https://openalex.org/W4282916849","https://openalex.org/W4360980513","https://openalex.org/W4366548479","https://openalex.org/W4377291442","https://openalex.org/W4381104201","https://openalex.org/W4385571645","https://openalex.org/W4388514671","https://openalex.org/W4389747800","https://openalex.org/W4391184004","https://openalex.org/W4391882779","https://openalex.org/W4393977362","https://openalex.org/W4398184456","https://openalex.org/W4398192428","https://openalex.org/W4398217745","https://openalex.org/W4399567757","https://openalex.org/W4399597451","https://openalex.org/W4400561411","https://openalex.org/W4401395578","https://openalex.org/W4402667158","https://openalex.org/W4402670429","https://openalex.org/W4402827393","https://openalex.org/W4402860127","https://openalex.org/W4403170101","https://openalex.org/W4404781852","https://openalex.org/W4404837928","https://openalex.org/W4404840084","https://openalex.org/W4405094054","https://openalex.org/W4406611872","https://openalex.org/W4407416402","https://openalex.org/W4413643828","https://openalex.org/W4413942089","https://openalex.org/W4414433399","https://openalex.org/W4414907014","https://openalex.org/W4415729392","https://openalex.org/W4415824546","https://openalex.org/W4417220482","https://openalex.org/W4417250729","https://openalex.org/W7130841482","https://openalex.org/W7131784069","https://openalex.org/W7131800114","https://openalex.org/W7131843000","https://openalex.org/W7148506278","https://openalex.org/W7154450389"],"related_works":["https://openalex.org/W4407632791","https://openalex.org/W7124645184","https://openalex.org/W7140255570","https://openalex.org/W4367692219","https://openalex.org/W7155540074","https://openalex.org/W4411119371","https://openalex.org/W4389544179","https://openalex.org/W4406236949","https://openalex.org/W7133340340","https://openalex.org/W4387561321"],"abstract_inverted_index":{"Large":[0],"Language":[1],"Models":[2],"(LLMs)":[3],"increasingly":[4],"support":[5],"time-consuming":[6],"conceptual":[7,122,258],"modeling":[8,123,259],"tasks":[9],"such":[10,51],"as":[11,52,78,220],"building":[12],"or":[13,62,88,106],"combining":[14,126],"models":[15],"from":[16,193],"text.":[17],"In":[18],"this":[19,74],"context,":[20],"causal":[21,29],"maps":[22],"are":[23,100,236],"labeled,":[24],"directed":[25],"graphs":[26],"that":[27,67,132,180,233,255],"represent":[28],"relationships":[30],"(edges)":[31],"between":[32],"selected":[33],"factors":[34],"(nodes)":[35],"in":[36,209],"a":[37,59,111,134],"problem":[38],"domain.":[39],"Modelers":[40],"control":[41,217],"the":[42,45,95,104,114,120,154,158,161,190,194,198,207,218,270],"output":[43],"through":[44,129],"LLM's":[46],"prompt":[47,234],"and":[48,54,86,148,173,186,228,280],"decoding":[49,87,241],"parameters":[50],"temperature,":[53],"recent":[55],"studies":[56,260,267],"either":[57],"use":[58,140],"default":[60],"temperature":[61],"minimize":[63],"it":[64,68],"by":[65,170,222],"expecting":[66],"supports":[69],"replicability.":[70],"However,":[71],"evidence":[72],"about":[73],"expectation":[75],"remains":[76],"limited,":[77,265],"does":[79],"our":[80,177,223,252],"understanding":[81],"of":[82,103,113,125,136,157,163,166,206,225,257,272],"how":[83],"different":[84,149],"LLMs":[85,142,185,262],"prompting":[89,137],"strategies":[90],"shape":[91],"results.":[92,210],"We":[93,117,139,231],"assess":[94],"extent":[96],"to":[97,151,204],"which":[98],"findings":[99,253],"an":[101],"artifact":[102],"LLM":[105,195],"its":[107],"variability":[108],"rather":[109],"than":[110],"reflection":[112],"modeler's":[115],"controls.":[116],"focus":[118],"on":[119,189],"common":[121],"task":[124],"models,":[127],"exemplified":[128],"three":[130],"algorithms":[131],"reflect":[133],"variety":[135],"techniques.":[138],"five":[141],"(DeepSeek,":[143],"Gemini,":[144],"GPT,":[145],"Qwen,":[146],"Ministral)":[147],"versions":[150],"account":[152],"for":[153,202],"potential":[155],"impact":[156],"architectures.":[159],"Using":[160],"Design":[162],"Experiments":[164],"approach":[165],"factorial":[167],"analyses":[168],"(supplemented":[169],"paired":[171],"tests":[172],"confidence":[174],"interval":[175],"checks),":[176],"results":[178],"show":[179],"outcomes":[181],"differ":[182],"significantly":[183],"across":[184],"versions.":[187],"Depending":[188],"algorithm,":[191],"randomness":[192],"can":[196],"be":[197,264],"dominating":[199],"factor,":[200],"responsible":[201],"up":[203],"96%":[205],"variation":[208],"This":[211],"happens":[212],"even":[213],"if":[214],"we":[215],"directly":[216],"decoding,":[219,278],"evidenced":[221],"comparison":[224],"greedy,":[226],"beam-search,":[227],"contrastive":[229],"decoding.":[230],"find":[232],"effects":[235],"systematic":[237],"but":[238,244],"metric-dependent,":[239],"while":[240],"affects":[242],"performance":[243,273],"there":[245],"is":[246],"no":[247],"universally":[248],"best":[249],"strategy.":[250],"Since":[251],"suggest":[254],"replicability":[256],"using":[261],"may":[263,268],"future":[266],"report":[269],"distribution":[271],"measures":[274],"alongside":[275],"exact":[276],"model,":[277],"replication,":[279],"baseline-normalization":[281],"settings.":[282]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-10-28T00:00:00"}
