{"id":"W4398654935","doi":"10.7910/dvn/ii5jzg/e6brju","title":"MSP_F_20_NFL_4_30.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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003027636,0.0003750956,0.0007671567,0.000260316,0.0001177646,0.0001879714,0.0009013199,0.0003114596,0.09058557],"category_scores_gemma":[0.0001211005,0.0004374894,0.0002284796,0.0002638753,0.00007584763,0.0002656077,0.0003621776,0.0005279866,0.6837317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008467474,"about_ca_system_score_gemma":0.00005695114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00086826,"about_ca_topic_score_gemma":0.00008612038,"domain_scores_codex":[0.9979063,0.000007059249,0.0008076711,0.000784162,0.00008599237,0.0004088442],"domain_scores_gemma":[0.9977132,0.00002199416,0.0006257737,0.001375976,0.00002836247,0.000234689],"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":[0.00001354847,0.00004572703,0.0001450537,0.0001060119,0.00009636897,0.00008104242,0.00001508147,0.0000201481,1.503869e-7,0.002593506,0.9968382,0.00004520889],"study_design_scores_gemma":[0.0003030814,0.00004655311,0.0001597606,0.00002824866,0.00003741089,0.000006512129,0.000009297359,0.0005601045,0.000001169319,0.0004097136,0.9979039,0.0005342148],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000959963,0.00001591799,0.00008829533,0.00003751239,0.001275978,0.0001744322,0.9955438,0.00004170726,0.002812706],"genre_scores_gemma":[0.00008852064,0.002544967,0.0001089707,0.00173327,0.0007337776,0.00001640989,0.9935562,0.00003885019,0.001179026],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5931461,"threshold_uncertainty_score":0.9998077,"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."}}