{"id":"W1504333795","doi":"","title":"Modeling Dependency in Prediction Markets","year":2010,"lang":"en","type":"article","venue":"The Faculty Digital Archive (New York University)","topic":"Sports Analytics and Performance","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"Dependency (UML); Prediction market; Revenue; Computer science; Raw data; Econometrics; Economics; Artificial intelligence; Finance","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001132185,0.0001060948,0.0001455302,0.0002475541,0.000115162,0.00008895596,0.0003353271,0.00004737893,0.0001323445],"category_scores_gemma":[0.00002186252,0.0001009437,0.00008693033,0.0002765067,0.00005113399,0.0004192667,0.00009164438,0.0002758331,0.000169333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003438803,"about_ca_system_score_gemma":0.00003041028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006145169,"about_ca_topic_score_gemma":0.0006237414,"domain_scores_codex":[0.999312,0.000003082773,0.0001960855,0.0002392698,0.00003937507,0.0002101373],"domain_scores_gemma":[0.9995916,0.00001842917,0.00007840386,0.000215503,0.00001086341,0.00008521106],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002421042,0.0002254709,0.4336187,0.00002188428,0.0001251832,0.00005443599,0.003050349,0.03904482,0.00004943285,0.5089964,0.003056158,0.01151511],"study_design_scores_gemma":[0.001300608,0.0000655763,0.1043516,0.00003159151,0.00001354058,0.00001403126,0.0007670486,0.5719036,0.000009800196,0.07444175,0.2466112,0.0004896769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8421699,0.00002476771,0.007683769,0.0002315894,0.0001957506,0.0001114741,0.0006022165,0.00003190518,0.1489487],"genre_scores_gemma":[0.9883179,0.00003222693,0.0001342541,0.00002841328,0.00007073477,2.680058e-7,0.00009978335,0.000008981253,0.01130746],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5328588,"threshold_uncertainty_score":0.4116364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02988971916987451,"score_gpt":0.1828962747301695,"score_spread":0.153006555560295,"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."}}