{"id":"W2736195052","doi":"10.1097/sla.0000000000002420","title":"Assessment of Conflicts of Interest in Robotic Surgical Studies","year":2017,"lang":"en","type":"article","venue":"Annals of Surgery","topic":"Pharmaceutical industry and healthcare","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kingston General Hospital; Queen's University","funders":"National Cancer Institute","keywords":"Payment; Transparency (behavior); Medicine; Odds ratio; Confidence interval; Conflict of interest; Statement (logic); MEDLINE; Actuarial science; Accounting; Law; Business; Finance; Political science; Pathology; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002689131,0.0001521371,0.0008734532,0.0001668923,0.00009853854,0.000004744379,0.0002919784,0.0003402901,0.0003299985],"category_scores_gemma":[0.0007355281,0.0001391015,0.0001904489,0.0001025632,0.0008302643,0.0001428925,0.0001657446,0.0007885884,0.000003820507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001401565,"about_ca_system_score_gemma":0.0001572216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008009157,"about_ca_topic_score_gemma":0.00003214146,"domain_scores_codex":[0.997934,0.0004827834,0.0009013864,0.0001932193,0.0001220414,0.0003665666],"domain_scores_gemma":[0.9961027,0.002351292,0.0006759086,0.0003145582,0.0003657163,0.0001898559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004269184,0.001001805,0.9678659,0.00137203,0.0004910894,0.0002162772,0.0003748052,0.0002213335,0.004615248,0.01041239,0.002978436,0.01002378],"study_design_scores_gemma":[0.001339543,0.0001910687,0.7873281,0.0008652774,0.0001093379,0.00001733461,0.0004567942,0.0006972744,0.1895381,0.001895076,0.01724859,0.0003135502],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894431,0.00227438,0.000001161683,0.004384583,0.0007310847,0.0001559709,0.00004948741,0.000008126593,0.002952107],"genre_scores_gemma":[0.9943367,0.00495866,0.00001411053,0.0004436877,0.00008664886,0.0000112707,0.000005621613,0.00000906017,0.000134205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1849228,"threshold_uncertainty_score":0.5672396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9583025357868539,"score_gpt":0.6959979318801287,"score_spread":0.2623046039067252,"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."}}