{"id":"W6964047844","doi":"10.25384/sage.19803142","title":"sj-docx-1-mdm-10.1177_0272989X221099493 – Supplemental material for Noninferiority Margin Size and Acceptance of Trial Results: Contingent Valuation Survey of Clinician Preferences for Noninferior Mortality","year":2022,"lang":"en","type":"article","venue":"Sage Journals Data","topic":"Ecology and biodiversity studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine; McMaster University; Institute for Clinical Evaluative Sciences; McGill University; Children's Hospital of Eastern Ontario; BC Children's Hospital; SickKids Foundation; University of Toronto; Sunnybrook Health Science Centre; University of British Columbia","funders":"","keywords":"Contingent valuation; Margin (machine learning); Medical decision making; Valuation (finance); Incentive","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004899611,0.0009406611,0.001001655,0.003642555,0.001148029,0.003706971,0.002167053,0.00248047,0.9317889],"category_scores_gemma":[0.08167615,0.001276476,0.0008082222,0.004960788,0.0005748489,0.003095181,0.001995522,0.002131572,0.6621422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002228295,"about_ca_system_score_gemma":0.003335209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01017971,"about_ca_topic_score_gemma":0.01851391,"domain_scores_codex":[0.9966668,0.0006220295,0.000539477,0.0002888837,0.001523504,0.0003591322],"domain_scores_gemma":[0.8987767,0.07003061,0.004944707,0.0044542,0.01781911,0.003974699],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007730096,0.00004923741,0.0003250636,0.000226532,0.000003439196,0.00001062164,0.00002075743,0.00005835294,0.0000407987,0.0002331601,0.993101,0.005853693],"study_design_scores_gemma":[0.001598288,0.0002347916,0.01493346,0.001570411,0.00003138893,0.0001604383,0.0004991535,0.001189168,0.0009070461,0.005979424,0.9727572,0.000139237],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006665824,0.00005550781,0.0009043571,0.001748448,0.0004536592,0.0005176219,0.9538261,0.00358663,0.03824094],"genre_scores_gemma":[0.01723924,0.0004610917,0.00866855,0.004347423,0.001137653,0.004603277,0.796897,0.009471966,0.1571738],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9317889,"threshold_uncertainty_score":0.09729493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1746255018299813,"score_gpt":0.3762298328072728,"score_spread":0.2016043309772915,"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."}}