{"id":"W4416089165","doi":"10.32731/ijsf.153.082020.02","title":"FIFA World Cup: A Case of (In)efficiency of the Betting Market","year":2020,"lang":"en","type":"article","venue":"International Journal of Sport Finance","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trinity College","funders":"","keywords":"Odds; Logit; Key (lock); Logistic regression; Process (computing); Nested logit","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":[],"consensus_categories":[],"category_scores_codex":[0.0004794748,0.00007664245,0.0003160309,0.0001944173,0.00001827042,0.00001177305,0.0004608878,0.00002672969,0.0003071854],"category_scores_gemma":[0.00005936003,0.0000660067,0.0001752639,0.0003410257,0.00005684588,0.0001568699,0.00005880448,0.0001762635,0.00000326571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003891266,"about_ca_system_score_gemma":0.00004896068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001415937,"about_ca_topic_score_gemma":0.00004473858,"domain_scores_codex":[0.9985586,0.000001682234,0.001121469,0.0001142298,0.000100944,0.0001030883],"domain_scores_gemma":[0.9980121,0.00001691997,0.00167034,0.0001127123,0.0001600408,0.000027837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007185881,0.00009762746,0.9676436,0.00002404657,0.0000409345,0.0003809586,0.0005189481,0.004204053,0.00001140454,0.02468213,0.0008105247,0.001513963],"study_design_scores_gemma":[0.001327273,0.000132741,0.8486025,0.0004361002,0.00001486202,0.0005425155,0.0001408486,0.04623466,0.001050183,0.003058161,0.09820941,0.0002507882],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9916644,0.000860735,0.0002179361,0.00164098,0.0005279066,0.00004652655,0.00004222419,0.00000119519,0.004998141],"genre_scores_gemma":[0.9986401,0.0002716142,0.0003206095,0.0002239089,0.0001450826,5.882004e-7,6.075383e-7,0.000006925242,0.0003906079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1190411,"threshold_uncertainty_score":0.3363465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02235645955995242,"score_gpt":0.230209265651949,"score_spread":0.2078528060919966,"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."}}