{"id":"W4398453869","doi":"10.7910/dvn/ii5jzg/7rttrp","title":"MSP_F_100_NFL_4_14.xlsx","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001206064,0.002408893,0.001513198,0.004656489,0.0008550367,0.00388601,0.003200714,0.002635946,0.3654161],"category_scores_gemma":[0.009757118,0.0009593597,0.001286732,0.0083306,0.0006067531,0.002432268,0.00306417,0.001761384,0.3582917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001788095,"about_ca_system_score_gemma":0.002307512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02773448,"about_ca_topic_score_gemma":0.03871751,"domain_scores_codex":[0.9986171,0.0002018637,0.0001679183,0.000322221,0.0003268361,0.0003641467],"domain_scores_gemma":[0.9965169,0.0008510882,0.0003673922,0.0007485867,0.001072705,0.000443254],"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":[0.00002556002,0.00001008846,0.0003439021,0.0002653897,0.000009809231,0.000005813135,0.0000103783,0.0000728973,0.00002869217,0.0002684696,0.9981067,0.0008523919],"study_design_scores_gemma":[0.0003080182,0.00001894521,0.003454247,0.0003197258,0.00001540883,0.00002904662,0.00009050227,0.0002358797,0.000224715,0.001143727,0.9941287,0.00003117722],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004027796,0.00001987519,0.00001924294,0.00005184889,0.0000176326,0.000004802901,0.9990401,0.0002152715,0.0005908788],"genre_scores_gemma":[0.0003016108,0.00003837067,0.0001397352,0.00006923934,0.00001537447,0.00005868499,0.9979171,0.0001470776,0.00131283],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6345839,"threshold_uncertainty_score":0.9051569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03145694927339215,"score_gpt":0.2131536742860324,"score_spread":0.1816967250126402,"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."}}