{"id":"W2900163858","doi":"10.25011/cim.v41i2.31419","title":"Curare: from laboratory to law court","year":2018,"lang":"en","type":"article","venue":"Clinical and investigative medicine","topic":"Cardiac, Anesthesia and Surgical Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Work (physics); Curare; Medicine; Management; Law; Library science; Anesthesia; Political science; Engineering","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":[0.006925531,0.0005209444,0.0007755015,0.001755581,0.01161284,0.01898145,0.003147358,0.01394122,0.1117683],"category_scores_gemma":[0.03420234,0.0005584347,0.0007620288,0.001132217,0.01002605,0.01215774,0.00892008,0.01898866,0.0176611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01155818,"about_ca_system_score_gemma":0.01597986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03023465,"about_ca_topic_score_gemma":0.04684064,"domain_scores_codex":[0.9906825,0.002171704,0.0005357951,0.001533368,0.003483618,0.00159291],"domain_scores_gemma":[0.9851074,0.004420187,0.000727335,0.001843926,0.004807343,0.003093686],"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":[0.00001501244,0.00002020286,0.0002991012,0.00005197926,0.000005948774,0.0004756197,0.0008260921,0.00004407764,0.0000835153,0.2259982,0.7437356,0.02844465],"study_design_scores_gemma":[0.000009593497,0.00001009409,0.0002766621,0.0003685195,0.000004875565,0.0003384802,0.001548158,0.00008865043,0.0001169827,0.05281175,0.9444085,0.00001786311],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.001871858,0.009627192,0.00311779,0.5973107,0.01957905,0.00008425085,0.0003081048,0.0002910211,0.3678101],"genre_scores_gemma":[0.09700011,0.0104767,0.002660905,0.4084749,0.01442925,0.000174613,0.0004013243,0.0007171149,0.465665],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1117683,"threshold_uncertainty_score":0.3739021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1373430187438738,"score_gpt":0.3743465452059975,"score_spread":0.2370035264621237,"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."}}