{"id":"W4233177078","doi":"10.1503/cmaj.080448","title":"Deaths","year":2008,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Manitoba","funders":"","keywords":"Computer science; World Wide Web; Data 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":[0.0006744228,0.0005561371,0.0005156049,0.001564885,0.001942543,0.001328657,0.001052243,0.001419021,0.4407528],"category_scores_gemma":[0.007608238,0.0002125632,0.0006969559,0.001481872,0.0002857211,0.0008998103,0.001385346,0.001989809,0.2259059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00141718,"about_ca_system_score_gemma":0.002545702,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01739172,"about_ca_topic_score_gemma":0.01780516,"domain_scores_codex":[0.9990155,0.0001437567,0.00008048332,0.0001468896,0.0003811127,0.0002322446],"domain_scores_gemma":[0.9974934,0.0002236122,0.0002259613,0.0003182397,0.001183472,0.0005553794],"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":[0.00004689688,0.00001281193,0.001162232,0.00007341831,0.000005792712,0.0001595954,0.00004882647,0.00001125029,0.00002943817,0.001908332,0.9691265,0.02741479],"study_design_scores_gemma":[0.00002536238,0.00002412626,0.004814042,0.0003890143,0.000008824713,0.0005502834,0.0001977033,0.00001995211,0.00006025216,0.001335834,0.9925647,0.000009846877],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005183751,0.009895104,0.001462872,0.04035252,0.02870951,0.0005372824,0.1037559,0.00258129,0.8075218],"genre_scores_gemma":[0.02459484,0.008296463,0.0007111797,0.01759913,0.004590235,0.0003980838,0.05846217,0.0004224762,0.8849253],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9826083,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009191702431247905,"score_gpt":0.2202276500865598,"score_spread":0.2110359476553119,"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."}}