{"id":"https://openalex.org/W7214244102","doi":"https://doi.org/10.48550/arxiv.2609.27234","title":"Discover, Falsify, Revise: Auditing Input-Use Claims from Source Code to Predictive Contribution in Agent-Discovered Cell Models","display_name":"Discover, Falsify, Revise: Auditing Input-Use Claims from Source Code to Predictive Contribution in Agent-Discovered Cell Models","publication_year":2026,"publication_date":"2026-09-23","ids":{"openalex":"https://openalex.org/W7214244102","doi":"https://doi.org/10.48550/arxiv.2609.27234"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.27234","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.27234","pdf_url":"https://arxiv.org/pdf/2609.27234","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.27234","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013536349","display_name":"Mengran Li","orcid":"https://orcid.org/0000-0001-7540-530X","observed_orcids":["https://orcid.org/0000-0001-7540-530X"]},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li, Mengran","raw_affiliation_strings":["Sun Yat-sen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5152619608","display_name":"Bo Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Li, Bo","raw_affiliation_strings":["University of Macau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Macau","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5152664367","display_name":"Chengyang Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Chengyang","raw_affiliation_strings":["Sichuan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5152758829","display_name":"Yang Yan","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan, Yang","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5152585124","display_name":"Jinfeng Xu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xu, Jinfeng","raw_affiliation_strings":["University of British Columbia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of British Columbia","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5152697180","display_name":"Zhenchao Tang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tang, Zhenchao","raw_affiliation_strings":["Tencent AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.43799999356269836,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.43799999356269836,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.2750999927520752,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.04179999977350235,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/falsification","display_name":"falsification","score":0.5709999799728394},{"id":"https://openalex.org/keywords/language-model-agents","display_name":"language model agents","score":0.8140000104904175},{"id":"https://openalex.org/keywords/dose-response-relationship","display_name":"dose-response relationship","score":0.3799999952316284}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5360999703407288},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4133000075817108},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40709999203681946},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4002000093460083},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.39989998936653137},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.3995000123977661},{"id":"https://openalex.org/C172205157","wikidata":"https://www.wikidata.org/wiki/Q1782962","display_name":"Model predictive control","level":3,"score":0.3930000066757202},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3889000117778778},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.3792000114917755},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.3668000102043152},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C117354338","wikidata":"https://www.wikidata.org/wiki/Q1165112","display_name":"Singleton","level":3,"score":0.351500004529953},{"id":"https://openalex.org/C72563966","wikidata":"https://www.wikidata.org/wiki/Q1303415","display_name":"Cohort","level":2,"score":0.34200000762939453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32010000944137573},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2939999997615814},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C122251271","wikidata":"https://www.wikidata.org/wiki/Q940039","display_name":"Ex-ante","level":2,"score":0.28220000863075256},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2702000141143799},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2689000070095062},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C20685875","wikidata":"https://www.wikidata.org/wiki/Q7239678","display_name":"Predictive validity","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.25189998745918274}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.27234","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.27234","pdf_url":"https://arxiv.org/pdf/2609.27234","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.27234","doi":"https://doi.org/10.48550/arxiv.2609.27234","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.27234","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,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.27234","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.27234","pdf_url":"https://arxiv.org/pdf/2609.27234","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,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214244102.pdf","grobid_xml":"https://content.openalex.org/works/W7214244102.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7223123247","https://openalex.org/W7202213229","https://openalex.org/W7169825925","https://openalex.org/W7213456819","https://openalex.org/W7155155517","https://openalex.org/W7214915937","https://openalex.org/W7155598843","https://openalex.org/W7196942820","https://openalex.org/W7166809731","https://openalex.org/W7137143648"],"abstract_inverted_index":{"AI":[0],"virtual":[1],"cells":[2],"aim":[3],"to":[4,8,99,236],"predict":[5],"cellular":[6],"responses":[7],"specified":[9],"interventions,":[10],"yet":[11],"held-out":[12,88,147,186],"predictive":[13,212],"performance":[14,187],"alone":[15],"does":[16,229],"not":[17,215],"establish":[18],"use":[19],"of":[20,72,94,132,218],"the":[21,57,119,175],"supplied":[22],"perturbation":[23,79],"information.":[24],"This":[25],"prediction-claim":[26],"gap":[27],"matters":[28],"in":[29],"agentic":[30,237],"model":[31,238],"discovery,":[32,239],"where":[33],"language-model":[34],"agents":[35],"generate":[36],"and":[37,66,118,188,192],"revise":[38],"predictors":[39],"using":[40],"score-based":[41],"feedback.":[42],"We":[43],"introduce":[44],"CELLAUDIT,":[45],"which":[46],"audits":[47],"input-use":[48,219],"claims":[49],"by":[50,114],"asking":[51],"whether":[52,60,67],"an":[53,82,207],"input":[54],"can":[55],"enter":[56],"cited":[58],"computation,":[59],"fitted":[61],"predictions":[62,141],"depend":[63],"on":[64,145,159,206],"it,":[65],"that":[68],"dependence":[69],"improves":[70],"prediction":[71],"observed":[73],"response.":[74],"On":[75,162],"a":[76,86,102,110,129,233],"paired":[77,199],"morphology-transcriptomics":[78],"benchmark":[80],"(BBBC047),":[81],"agent-selected":[83],"predictor":[84,104],"attains":[85],"mean":[87,168,190],"Global":[89],"Pearson":[90],"correlation":[91],"coefficient":[92],"(PCC)":[93],"0.3153":[95],"but":[96,149],"remains":[97],"invariant":[98],"compound":[100,143,169,191,227],"replacement;":[101],"control-profile-only":[103,176],"reaches":[105],"0.3142.":[106],"Source":[107],"inspection":[108],"identifies":[109],"compound-query":[111],"pathway":[112],"blocked":[113],"singleton":[115],"key-value":[116],"attention,":[117],"invariance":[120],"persists":[121],"after":[122],"refitting":[123],"with":[124,155],"disjoint":[125],"control":[126],"wells.":[127],"In":[128,178],"stratified":[130],"audit":[131],"48":[133],"candidates":[134],"across":[135,195],"two":[136],"linked":[137],"tasks,":[138],"47":[139],"change":[140],"under":[142],"replacement":[144],"both":[146,160],"folds,":[148],"only":[150],"20":[151],"show":[152],"target-loss":[153],"gains":[154,173],"intervals":[156,200],"above":[157],"zero":[158],"folds.":[161],"BBBC047,":[163],"falsification-guided":[164],"revisions":[165],"recover":[166],"positive":[167],"contributions":[170,194],"while":[171],"retaining":[172],"over":[174],"baseline.":[177],"matched":[179],"sci-Plex":[180],"searches,":[181],"audit-enriched":[182],"feedback":[183],"yields":[184],"higher":[185],"larger":[189],"dose":[193,221],"five":[196],"trajectories,":[197],"although":[198],"span":[201],"zero.":[202],"Refitting":[203],"fixed":[204],"designs":[205],"independently":[208],"acquired":[209],"cohort":[210],"shows":[211],"generalization":[213,217],"need":[214],"imply":[216],"claims:":[220],"contribution":[222],"persists,":[223],"whereas":[224],"support":[225],"for":[226],"identity":[228],"not.":[230],"CELLAUDIT":[231],"adds":[232],"falsification":[234],"layer":[235],"moving":[240],"from":[241],"generate-score-revise":[242],"toward":[243],"discover-falsify-revise.":[244]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-09-25T00:00:00"}