{"id":"W4410336353","doi":"10.1186/s41073-025-00164-0","title":"Research on policy mechanisms to address funding bias and conflicts of interest in biomedical research: a scoping review","year":2025,"lang":"en","type":"review","venue":"Research Integrity and Peer Review","topic":"Pharmaceutical industry and healthcare","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"U.S. National Library of Medicine; National Institute of General Medical Sciences","keywords":"Conflict of interest; Political science; Management science; Public relations; Engineering ethics; Economics; Engineering; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["metaresearch","research_integrity"],"domain":"incentives","study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["metaresearch","research_integrity"],"domain":"incentives","study_design":"systematic_review","genre":"review","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","research_integrity"],"category_scores_codex":[0.1473637,0.0007197057,0.004270055,0.004364772,0.0008481689,0.0001321074,0.0017339,0.0024166,0.001087575],"category_scores_gemma":[0.06506041,0.0005686487,0.0003630357,0.008788653,0.00213564,0.0001467559,0.00251634,0.03759196,0.0002437498],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008070603,"about_ca_system_score_gemma":0.005038619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008451713,"about_ca_topic_score_gemma":0.0003655236,"domain_scores_codex":[0.9473125,0.04271347,0.002667989,0.001704215,0.002726099,0.002875715],"domain_scores_gemma":[0.9602922,0.03122833,0.0003437246,0.001139495,0.004008885,0.002987371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006684933,0.0002447952,0.00000197437,0.5019943,0.00008216542,0.0001160362,0.0001049963,1.945823e-8,0.000003355199,0.02868346,0.02361383,0.4450882],"study_design_scores_gemma":[0.0002061673,0.000374457,0.0000010167,0.4847133,0.00009922965,0.00003842868,0.00006379286,0.000002320381,0.00001528091,0.0008840082,0.5133937,0.0002082778],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001601169,0.9304728,0.000002479139,0.05336383,0.0002610325,0.01061553,0.0005510664,0.00003148795,0.004685767],"genre_scores_gemma":[0.00009488783,0.9903588,0.00004131506,0.004533336,0.0004028478,0.001987303,0.0001633208,0.00005806336,0.002360107],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.4897799,"threshold_uncertainty_score":0.9998255,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9766357963041572,"score_gpt":0.7866428425180303,"score_spread":0.1899929537861269,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}