{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00123049,0.002465798,0.001525061,0.004602947,0.000833868,0.00400108,0.003187607,0.002548791,0.3997796],"category_scores_gemma":[0.01017402,0.0009845218,0.001296222,0.008264795,0.0006057755,0.002584212,0.003210859,0.001762775,0.3833004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001807176,"about_ca_system_score_gemma":0.002314379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02723863,"about_ca_topic_score_gemma":0.03688857,"domain_scores_codex":[0.9986342,0.0001967456,0.0001650443,0.0003198958,0.0003160694,0.000368059],"domain_scores_gemma":[0.9963619,0.0009136543,0.0003778482,0.0007646743,0.001102872,0.0004791078],"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":[0.00002599359,0.000009778537,0.0003297842,0.0002708654,0.000009696289,0.000005738372,0.00001077426,0.00007037714,0.00002866397,0.0002661213,0.9981389,0.0008331843],"study_design_scores_gemma":[0.0003188775,0.00001986985,0.003371641,0.0003282063,0.0000154312,0.00002934894,0.00009308787,0.0002340284,0.0002255957,0.001216974,0.9941147,0.00003211697],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00003663464,0.00001802126,0.00001915534,0.00005117809,0.00001695584,0.000004687732,0.9990387,0.0002215997,0.0005931301],"genre_scores_gemma":[0.0002992608,0.00003775804,0.0001401052,0.00007275708,0.00001582696,0.00005998182,0.9978593,0.0001620785,0.001352911],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6002204,"threshold_uncertainty_score":0.8561415,"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."}}