{"id":"W4398316788","doi":"10.7910/dvn/ii5jzg/bjf1oq","title":"MSP_F_20_NFL_4_15.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":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003005145,0.0003753625,0.0007665898,0.0002602346,0.0001182475,0.0001911009,0.0009011018,0.0003118055,0.08807952],"category_scores_gemma":[0.0001217065,0.0004377917,0.0002286282,0.0002640043,0.0000758586,0.0002664719,0.0003625496,0.0005290735,0.6818681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000850954,"about_ca_system_score_gemma":0.00005690724,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008014097,"about_ca_topic_score_gemma":0.00008280564,"domain_scores_codex":[0.9979045,0.000007065685,0.0008075506,0.0007850273,0.00008638687,0.0004094841],"domain_scores_gemma":[0.9977114,0.00002224313,0.0006255733,0.001377408,0.00002837841,0.0002349694],"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":[0.00001345783,0.0000450529,0.0001302939,0.000105723,0.00009707615,0.00008092207,0.00001518418,0.00002790738,1.318746e-7,0.002406096,0.9970309,0.0000472456],"study_design_scores_gemma":[0.000304283,0.00004553502,0.0001501652,0.00002832754,0.00003712335,0.000006479138,0.000009645369,0.0007086606,0.000001004193,0.0003974569,0.9977768,0.0005345028],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009416002,0.00001632769,0.00008842828,0.00003935315,0.001068161,0.0001743966,0.9957697,0.00004177364,0.002792458],"genre_scores_gemma":[0.0000903041,0.002570493,0.0001078434,0.001763379,0.0007456823,0.00001557764,0.9934846,0.00003885583,0.001183312],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5937886,"threshold_uncertainty_score":0.9998074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03266678251959321,"score_gpt":0.2127360703839758,"score_spread":0.1800692878643826,"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."}}