{"id":"W4398610956","doi":"10.7910/dvn/ii5jzg/da97so","title":"MSP_F_150_NFL_4_19.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":[0.001171625,0.002384829,0.001527788,0.004495236,0.0008494229,0.004039668,0.003148688,0.002560908,0.4143247],"category_scores_gemma":[0.01003521,0.0009757933,0.001238401,0.008258965,0.0005980594,0.00259165,0.003160871,0.001733058,0.3851021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001841005,"about_ca_system_score_gemma":0.002310783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02741831,"about_ca_topic_score_gemma":0.03679671,"domain_scores_codex":[0.9986961,0.000186229,0.000158922,0.0003119103,0.0002953414,0.0003514389],"domain_scores_gemma":[0.9964119,0.0009389671,0.0003817742,0.0007350773,0.001069608,0.0004627105],"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":[0.00002604827,0.000009902613,0.000343397,0.0002800127,0.000009594464,0.000005761311,0.00001088953,0.00006870879,0.00002740697,0.0002775288,0.9980839,0.0008568098],"study_design_scores_gemma":[0.00032148,0.00001935279,0.003553539,0.0003499325,0.00001568058,0.00002903301,0.00009569,0.0002216743,0.0002188528,0.001220177,0.9939224,0.00003204495],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003675617,0.00001873432,0.00001853188,0.00005222198,0.00001699127,0.000004635026,0.9990138,0.0002012687,0.0006370321],"genre_scores_gemma":[0.0003232019,0.00004118894,0.0001378967,0.00007705514,0.00001667337,0.000062983,0.9977157,0.000159832,0.001465442],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5856754,"threshold_uncertainty_score":0.8353947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03240105477836171,"score_gpt":0.2128276324489748,"score_spread":0.1804265776706131,"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."}}