{"id":"W7105145023","doi":"10.71781/31874","title":"Prédiction de la performance au hockey sur glace avec des évaluations de terrain","year":2020,"lang":"fr","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Sports injuries and prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistical analysis; Snow cover; Climatic variability","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":[0.002536736,0.001681152,0.001077115,0.001139536,0.0004575089,0.001771686,0.0006818842,0.0009035048,0.005390964],"category_scores_gemma":[0.005964596,0.0004918883,0.001163413,0.001063825,0.0005548629,0.0006694089,0.0008201114,0.0007827854,0.002029444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005982766,"about_ca_system_score_gemma":0.001335337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02891553,"about_ca_topic_score_gemma":0.04090397,"domain_scores_codex":[0.9984033,0.000484895,0.00009065024,0.0004333029,0.0003713212,0.0002164766],"domain_scores_gemma":[0.9967693,0.001477421,0.0004727777,0.000185021,0.0008715185,0.0002238489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003120112,0.0008252709,0.7698577,0.00152664,0.001360433,0.000359714,0.002491183,0.03590024,0.02553728,0.0005916403,0.002293132,0.1561366],"study_design_scores_gemma":[0.00005446475,0.00152641,0.96552,0.000204253,0.0002330875,0.0001043785,0.001414148,0.02323766,0.003937342,0.0003791912,0.003310332,0.00007863565],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743325,0.0007525657,0.01833113,0.0001598072,0.0001065427,0.0003046788,0.001641514,0.0001939497,0.004177464],"genre_scores_gemma":[0.977249,0.0006565768,0.01062952,0.00007259755,0.0000436816,0.0004571434,0.0025235,0.00006042318,0.00830751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02891553,"threshold_uncertainty_score":0.05749446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006866625350520173,"score_gpt":0.2049271992115006,"score_spread":0.1980605738609804,"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."}}