{"id":"W4382601701","doi":"10.5539/ijef.v15n8p14","title":"Smart Money in the NCAA Men’s Basketball Tournament","year":2023,"lang":"en","type":"article","venue":"International Journal of Economics and Finance","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tournament; Basketball; Lottery; Bracket; Portfolio; Economics; Advertising; Microeconomics; Business; Financial economics; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001396269,0.0002052737,0.0002558746,0.0004469391,0.001357074,0.002276471,0.0003503604,0.0007015801,0.009542953],"category_scores_gemma":[0.004473448,0.00008618052,0.0001198583,0.0004881812,0.0006555055,0.001075045,0.0008959796,0.0008304086,0.000972166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284948,"about_ca_system_score_gemma":0.0009414011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02342989,"about_ca_topic_score_gemma":0.06505658,"domain_scores_codex":[0.9992849,0.0002784881,0.00002197462,0.00007360523,0.0001844167,0.0001566453],"domain_scores_gemma":[0.9987357,0.0002739296,0.0001146061,0.00004777858,0.0001324602,0.0006954265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005340643,0.002683894,0.2185953,0.0001629006,0.0002118205,0.001934579,0.003201908,0.04809239,0.002724444,0.2165479,0.2163155,0.2841888],"study_design_scores_gemma":[0.0007239539,0.002850707,0.4945686,0.000193504,0.0001145082,0.0004273027,0.01297783,0.1518309,0.004272769,0.1257437,0.2060188,0.0002774203],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8795549,0.0002323297,0.002161162,0.004103482,0.000273126,0.00004649293,0.0004386014,0.0001198084,0.1130701],"genre_scores_gemma":[0.9814463,0.00007949668,0.0006759932,0.0001831238,0.00004254384,0.00001491971,0.0002081692,0.00001184484,0.01733764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02342989,"threshold_uncertainty_score":0.04658705,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02832502971114578,"score_gpt":0.2295029103246456,"score_spread":0.2011778806134998,"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."}}