{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008474014,0.0004677806,0.0007999552,0.000783575,0.01540714,0.009198364,0.001363779,0.0119031,0.006855445],"category_scores_gemma":[0.01725311,0.0006346086,0.0005064602,0.0005703926,0.027509,0.01027918,0.00443594,0.02328447,0.002010196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0127243,"about_ca_system_score_gemma":0.02412251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1062039,"about_ca_topic_score_gemma":0.2367477,"domain_scores_codex":[0.9938753,0.002209453,0.0001368231,0.0007675386,0.001938281,0.001072542],"domain_scores_gemma":[0.9924919,0.003001518,0.0002464026,0.0003573071,0.00156236,0.002340494],"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":[0.00001268596,0.00001000995,0.00007496843,0.00002000053,0.000003381582,0.0001132234,0.002904121,0.00002725284,0.00005920523,0.1610079,0.8304767,0.005290573],"study_design_scores_gemma":[0.00000907166,0.000008776939,0.0001430905,0.0001391512,0.000004115779,0.00009535299,0.002535777,0.00003265603,0.00009091914,0.0460032,0.950913,0.00002499504],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0008410381,0.01792604,0.0006479922,0.9347883,0.01223867,0.000009261095,0.00001582586,0.00003613214,0.03349671],"genre_scores_gemma":[0.06674103,0.01210099,0.001376539,0.7290835,0.008645035,0.00006341427,0.00002390885,0.0001430986,0.1818225],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1062039,"threshold_uncertainty_score":0.2111713,"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."}}