{"id":"W6945028861","doi":"10.25318/3510011501-fra","title":"Nombre d'événements dans les causes actives devant les tribunaux civils, selon le type d'événement, Canada et certaines provinces et territoires","year":2019,"lang":"fr","type":"dataset","venue":"Statistics Canada Dissemination","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Context (archaeology); Legislation; Power (physics); State (computer science)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001597282,0.001297538,0.001348249,0.006697389,0.001482898,0.00263273,0.002634593,0.00140778,0.0324195],"category_scores_gemma":[0.02083785,0.00083355,0.001317055,0.01633149,0.0005990215,0.001325661,0.002006151,0.002535383,0.02258395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009110636,"about_ca_system_score_gemma":0.02160742,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7799394,"about_ca_topic_score_gemma":0.8415833,"domain_scores_codex":[0.9979708,0.0001725482,0.0003911109,0.0003843993,0.0006043011,0.0004767844],"domain_scores_gemma":[0.9889979,0.002241303,0.0008611351,0.001129875,0.005914633,0.000855275],"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":[0.00004658031,0.000009046831,0.004460421,0.000499053,0.00003461793,0.00001527987,0.0000546281,0.000149648,0.0000336228,0.0005343486,0.9924256,0.001737162],"study_design_scores_gemma":[0.0002247893,0.00001032468,0.07294218,0.0009648431,0.00007946073,0.00008253456,0.0006459591,0.0003977385,0.0002940469,0.001143569,0.9231436,0.00007084699],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001351743,0.00003272529,0.00002020209,0.00005806765,0.00001325432,0.000005781531,0.9993218,0.00003220469,0.000380739],"genre_scores_gemma":[0.0009820255,0.0001015545,0.0001627916,0.00005007422,0.000007165161,0.0000712187,0.9974837,0.00002714029,0.001114379],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2200606,"threshold_uncertainty_score":0.4427132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04728142641290973,"score_gpt":0.3452581192584436,"score_spread":0.2979766928455339,"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."}}