{"id":"W3014530657","doi":"10.3390/stats3020008","title":"The Prediction of Batting Averages in Major League Baseball","year":2020,"lang":"en","type":"article","venue":"Stats","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Luck; League; Ball (mathematics); Econometrics; Component (thermodynamics); Computer science; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.001732024,0.00042175,0.0003712343,0.0007958576,0.0001815875,0.001361584,0.0005233986,0.0005819399,0.001223037],"category_scores_gemma":[0.006872016,0.0002315499,0.0002843338,0.0009053081,0.0002532718,0.0007598777,0.000432231,0.001074283,0.000875363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009166207,"about_ca_system_score_gemma":0.0007187271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04337176,"about_ca_topic_score_gemma":0.04680415,"domain_scores_codex":[0.9996163,0.00009745937,0.00002134658,0.00009932691,0.0001156003,0.00004994409],"domain_scores_gemma":[0.9974799,0.001019968,0.0005875577,0.0001528974,0.0005311352,0.0002286228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003766559,0.0001622082,0.3148894,0.00005108443,0.00007554262,0.0001409307,0.0001033097,0.6387992,0.001171278,0.002975036,0.008350284,0.03290513],"study_design_scores_gemma":[0.00001146514,0.00007469259,0.08101302,0.00001963176,0.000008704184,0.00001706028,0.00009459018,0.9144716,0.001386667,0.001618435,0.001267533,0.00001656269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9653917,0.0002078061,0.02126527,0.0005694341,0.00009490197,0.00003196904,0.006395595,0.0006317221,0.005411585],"genre_scores_gemma":[0.9916162,0.00009121857,0.002636756,0.00002183632,0.00002447678,0.000008156463,0.004498941,0.00002754994,0.001074857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04337176,"threshold_uncertainty_score":0.08623862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04301146415228031,"score_gpt":0.2128941975765797,"score_spread":0.1698827334242994,"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."}}