{"id":"W6982932990","doi":"","title":"2017 11 18 La semaine no 12 dans la NFL avec Mark Dickey","year":2017,"lang":"fr","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistical analysis; Football; Sample (material); Period (music)","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":[0.002363497,0.0003426598,0.0002836234,0.003032926,0.001234429,0.003542583,0.0003866033,0.0008873964,0.08615148],"category_scores_gemma":[0.00597902,0.0002438077,0.0003307094,0.002705437,0.0008010872,0.001566628,0.001337696,0.001541345,0.02628692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003001291,"about_ca_system_score_gemma":0.002426788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07654089,"about_ca_topic_score_gemma":0.08715308,"domain_scores_codex":[0.9984818,0.0002371302,0.0000740856,0.0002306427,0.000756744,0.000219558],"domain_scores_gemma":[0.9975552,0.0005818772,0.0003666269,0.0001621924,0.0008676315,0.0004665111],"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":[0.0001664899,0.00004877905,0.01669122,0.0001355087,0.00002012545,0.0004035748,0.001084056,0.0005040333,0.0005025914,0.06650896,0.7040515,0.2098832],"study_design_scores_gemma":[0.000006753241,0.00001882616,0.02011566,0.0001664168,0.000005042416,0.0001971491,0.0007067382,0.0003311679,0.0002621921,0.004180901,0.9739924,0.0000167711],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.05572858,0.04100602,0.01567375,0.1068222,0.0102364,0.0001247018,0.02033993,0.001505229,0.7485632],"genre_scores_gemma":[0.1012262,0.009729558,0.003783673,0.001488565,0.002461069,0.00005086237,0.004287265,0.0005650744,0.8764077],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.08615148,"threshold_uncertainty_score":0.2882054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008970598620096647,"score_gpt":0.1810098876286597,"score_spread":0.1720392890085631,"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."}}