{"id":"W4398634251","doi":"10.7910/dvn/ii5jzg/lvk4hm","title":"MSP_F_20_NFL_4_32.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":"Materials 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":[0.0003025723,0.0003749262,0.0007650583,0.0002589592,0.0001181304,0.0001911235,0.0009002123,0.0003101652,0.08906053],"category_scores_gemma":[0.0001210036,0.0004372678,0.0002283733,0.0002636369,0.00007565322,0.0002758324,0.000361078,0.0005284378,0.6893501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008487071,"about_ca_system_score_gemma":0.00005677903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007940299,"about_ca_topic_score_gemma":0.00008437076,"domain_scores_codex":[0.9979081,0.000007069534,0.0008059749,0.0007837347,0.00008625288,0.000408891],"domain_scores_gemma":[0.9977172,0.00002224451,0.0006236552,0.001373885,0.00002833214,0.000234686],"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":[0.00001368074,0.0000449661,0.0001319934,0.0001062244,0.0000970123,0.00008007429,0.00001479519,0.00002092664,1.413594e-7,0.002589055,0.9968548,0.00004629623],"study_design_scores_gemma":[0.0003034733,0.00004577098,0.0001551505,0.00002824218,0.00003718599,0.000006516424,0.000009275883,0.0005860255,0.000001143251,0.0004058413,0.9978874,0.0005340168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009748164,0.00001432891,0.0000901608,0.00003893562,0.001284144,0.0001740589,0.9955009,0.00004172975,0.00284604],"genre_scores_gemma":[0.00009035808,0.002526371,0.0001065554,0.001761298,0.0007421995,0.00001638201,0.9934845,0.00003880242,0.001233561],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6002895,"threshold_uncertainty_score":0.9998079,"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."}}