{"id":"W1991045705","doi":"10.1111/anzs.12109","title":"A Simulator for Twenty20 Cricket","year":2015,"lang":"en","type":"article","venue":"Australian & New Zealand Journal of Statistics","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cricket; Statistics; Bayes' theorem; Simulation; Mathematics; Computer science; Bayesian probability","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":[0.0005097226,0.0001228997,0.0003932389,0.0001545657,0.0000378496,0.00008450252,0.0001771806,0.00006333647,0.0002625412],"category_scores_gemma":[0.000148752,0.0001175204,0.00009641117,0.0001082431,0.00002889229,0.0001665161,0.00001235285,0.0001365975,0.00006354882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005961093,"about_ca_system_score_gemma":0.0001159713,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001373175,"about_ca_topic_score_gemma":0.00001588429,"domain_scores_codex":[0.9987283,0.000003677128,0.0008187879,0.0001244458,0.0000734955,0.0002512723],"domain_scores_gemma":[0.9984964,0.00005316302,0.0007634908,0.0001348023,0.0001818942,0.0003702162],"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":[0.00009313737,0.00007124226,0.06823471,0.00002015756,0.00009205531,0.00002794396,0.0004464876,0.002946182,0.000001379921,0.03150558,0.8954048,0.001156316],"study_design_scores_gemma":[0.001927999,0.00058347,0.01102791,0.00002096152,0.00003483774,0.00003687012,0.00007195279,0.003622309,0.00001483185,0.06748992,0.9149827,0.0001861994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4517654,0.002919414,0.5019895,0.01902159,0.01130303,0.001124543,0.007825698,0.00005997523,0.003990863],"genre_scores_gemma":[0.9307241,0.0002169346,0.0232047,0.0002993702,0.001079935,0.000001272817,0.00003649934,0.00003344119,0.04440372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4789588,"threshold_uncertainty_score":0.4792343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0983534907435997,"score_gpt":0.2878016033870167,"score_spread":0.189448112643417,"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."}}