{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000233735,0.00004752912,0.0001212249,0.00003685942,0.00004793049,0.00001885603,0.00008903831,0.00002282684,0.0002199106],"category_scores_gemma":[0.00005142731,0.00004229065,0.00003347367,0.0001322022,0.0000220508,0.00007170188,0.00002132286,0.00007688574,0.00004151048],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001466202,"about_ca_system_score_gemma":0.000008610159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001392719,"about_ca_topic_score_gemma":0.00004926592,"domain_scores_codex":[0.9994018,0.000002932324,0.0003340559,0.0001239095,0.00002187081,0.0001154073],"domain_scores_gemma":[0.9996865,0.00002927729,0.000145789,0.00009764087,0.00001146229,0.0000292679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003529266,0.00003369099,0.9294154,0.0000659947,0.00003354822,0.000005615257,0.001815612,0.002912892,0.0000540952,0.05652908,0.004642865,0.004455938],"study_design_scores_gemma":[0.0008196373,0.0001388565,0.6187401,0.00003044997,0.000004914889,8.426092e-7,0.0003635156,0.2284822,0.00049343,0.004856896,0.1458871,0.0001820797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729224,0.001236913,0.001183319,0.002261415,0.0002945711,0.0001256774,0.0002381055,0.00001544989,0.02172211],"genre_scores_gemma":[0.9988755,0.0004042003,0.00005298983,0.0001648472,0.00006850465,0.000002941486,0.000007955558,0.000006385496,0.0004166771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3106753,"threshold_uncertainty_score":0.2407866,"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."}}