{"id":"W4398610682","doi":"10.7910/dvn/ii5jzg/oib6ud","title":"MSP_F_100_NFL_4_34.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":[0.001181965,0.002439785,0.001521644,0.004693374,0.0008445844,0.003870981,0.003156559,0.002641058,0.3780901],"category_scores_gemma":[0.009609706,0.0009635377,0.001277753,0.008352231,0.0006111215,0.002450482,0.003017245,0.001754768,0.3636102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001780301,"about_ca_system_score_gemma":0.002222721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02668635,"about_ca_topic_score_gemma":0.03654916,"domain_scores_codex":[0.9986728,0.0001921613,0.0001620289,0.0003096221,0.0003098316,0.0003535227],"domain_scores_gemma":[0.996568,0.0008717368,0.0003639854,0.0007216845,0.001038312,0.0004362221],"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":[0.000026095,0.00001051267,0.0003487342,0.0002879797,0.00001007433,0.000006046415,0.00001070665,0.00007599582,0.00003013418,0.0002646993,0.998058,0.0008710435],"study_design_scores_gemma":[0.0003203484,0.00002019559,0.003545671,0.0003364172,0.00001574704,0.00003074349,0.00009368641,0.0002448987,0.0002310855,0.001148422,0.9939806,0.0000321093],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003974316,0.00002002309,0.00001867825,0.00005080834,0.00001683281,0.000004742463,0.9990727,0.0002111022,0.0005654072],"genre_scores_gemma":[0.0003107003,0.00004034625,0.0001410685,0.0000699174,0.00001551516,0.00005974651,0.9979244,0.0001487642,0.00128939],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6219099,"threshold_uncertainty_score":0.887079,"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."}}