{"id":"W1520704500","doi":"","title":"Racing Matches and Games","year":2009,"lang":"en","type":"article","venue":"","topic":"Sport and Mega-Event Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gold rush; Advertising; Population; Geography; History; Demography; Business; Sociology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005198905,0.0003583036,0.0003332527,0.001294505,0.004210213,0.002022426,0.0005012061,0.0006704678,0.037126],"category_scores_gemma":[0.001816698,0.0002333845,0.0002331476,0.001558882,0.0005764763,0.0005955779,0.001964374,0.0006090176,0.005056742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002282613,"about_ca_system_score_gemma":0.002718586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2481628,"about_ca_topic_score_gemma":0.5662158,"domain_scores_codex":[0.9989845,0.0001376427,0.00003628503,0.00008618832,0.0003710594,0.0003842544],"domain_scores_gemma":[0.9987826,0.00005132404,0.0001031588,0.00004717239,0.0003427889,0.0006729881],"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":[0.0007866615,0.001477988,0.1810515,0.000672365,0.0001706239,0.0006875224,0.01078373,0.00128786,0.002474515,0.01662352,0.3265149,0.4574686],"study_design_scores_gemma":[0.00001822427,0.0002427389,0.5489242,0.0003064697,0.00001912595,0.0002635406,0.01122453,0.0001989195,0.0002972531,0.001774026,0.4366969,0.00003420261],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3165434,0.0054133,0.0009111966,0.006050698,0.0007630093,0.0002698112,0.005006711,0.0003169356,0.664725],"genre_scores_gemma":[0.6810748,0.006550893,0.001596824,0.002050824,0.0006045309,0.000158547,0.003523921,0.0001033643,0.3043363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2481628,"threshold_uncertainty_score":0.4934367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02311535895039883,"score_gpt":0.3304660651292723,"score_spread":0.3073507061788734,"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."}}