{"id":"W1997163794","doi":"10.1503/cmaj.120307","title":"Making a noble case for Till and McCulloch","year":2012,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Biomedical Ethics and Regulation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Data science; Library science; World Wide Web; Computer science; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002124586,0.00006819883,0.000149587,0.0001175313,0.0002679672,0.00003463071,0.00003177283,0.0004669303,0.0007728038],"category_scores_gemma":[0.001146389,0.00005418969,0.00006035217,0.0001068281,0.00007751285,0.00007987234,0.000007727898,0.0005624118,0.00001314653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004075843,"about_ca_system_score_gemma":0.001010323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003465891,"about_ca_topic_score_gemma":0.002698939,"domain_scores_codex":[0.998624,0.00004417587,0.0002424655,0.00007709963,0.0006051628,0.0004071159],"domain_scores_gemma":[0.9975457,0.0001402359,0.0001042436,0.00004571435,0.0002585706,0.001905561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004994118,0.0001679714,0.1158606,0.0002422919,0.0004774426,0.002925887,0.003535129,9.692593e-7,0.0001094392,0.01595614,0.2128001,0.6478742],"study_design_scores_gemma":[0.001681975,0.00008748333,0.02521376,0.00014298,0.00009518714,0.02375417,0.0004700858,0.001635883,0.000008326338,0.0006684886,0.9461352,0.0001064345],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4271815,0.00381174,0.008264515,0.546742,0.004138918,0.000834444,0.00007315867,0.00005755038,0.008896254],"genre_scores_gemma":[0.9840832,0.00005805213,0.001096786,0.01155328,0.002696237,0.000005216933,0.000007766406,0.00001159881,0.0004879077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7333352,"threshold_uncertainty_score":0.846166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03246775333816318,"score_gpt":0.3221797835108333,"score_spread":0.2897120301726701,"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."}}