{"id":"W1990518849","doi":"10.7202/1013726ar","title":"L’effet de la Loi C-68 sur les homicides au Québec : une analyse des bornes extrêmes","year":2013,"lang":"fr","type":"article","venue":"Criminologie","topic":"Gun Ownership and Violence Research","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Humanities; Art; Political science","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":[0.00111405,0.0004145652,0.0004128727,0.001082731,0.001229585,0.0008438424,0.0006349483,0.0005535914,0.003583352],"category_scores_gemma":[0.003239198,0.0001884859,0.0007219466,0.001513783,0.0007798534,0.0003507085,0.0005673362,0.0009594927,0.0002869208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008741396,"about_ca_system_score_gemma":0.005357586,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9417787,"about_ca_topic_score_gemma":0.9704359,"domain_scores_codex":[0.9988433,0.0003202907,0.0000487929,0.0001354375,0.0003650847,0.0002870772],"domain_scores_gemma":[0.9965719,0.0008644401,0.0008696113,0.0001072716,0.00112363,0.0004631963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005884296,0.0001189784,0.9622878,0.0001761404,0.0005649808,0.0001616253,0.002447378,0.000967215,0.0009535577,0.0002305545,0.00131006,0.03019335],"study_design_scores_gemma":[0.000007312616,0.0001547726,0.9967231,0.00005125721,0.00008433872,0.00001970618,0.0009437345,0.0001778638,0.0001208525,0.00001923436,0.001688829,0.000008968179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927873,0.001734602,0.0002346898,0.0004621642,0.00001758159,0.00004738945,0.001441719,0.000007246409,0.003267293],"genre_scores_gemma":[0.9927951,0.00118117,0.000271541,0.0002348259,0.00001376509,0.00005611918,0.0008234987,0.000005092495,0.004618803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05822134,"threshold_uncertainty_score":0.1171284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4217642360576996,"score_gpt":0.4385223781636813,"score_spread":0.0167581421059817,"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."}}