{"id":"W3123420865","doi":"10.1016/s0927-5398(02)00051-8","title":"A Bayesian analysis of dual trader informativeness in futures markets","year":2003,"lang":"en","type":"article","venue":"Journal of Empirical Finance","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Purdue University","keywords":"Futures contract; Dual (grammatical number); Economics; Intuition; Trading strategy; Private information retrieval; Profit (economics); Econometrics; Microeconomics; Bayesian probability; Financial economics; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0183725,0.001247186,0.003647473,0.003121185,0.001288195,0.00461083,0.003904632,0.00384298,0.00549862],"category_scores_gemma":[0.07306206,0.002882406,0.002190191,0.002508648,0.004190219,0.009816952,0.002781826,0.004537757,0.0004859707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001910522,"about_ca_system_score_gemma":0.001726637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006641509,"about_ca_topic_score_gemma":0.005776093,"domain_scores_codex":[0.9964769,0.0018957,0.000155345,0.0005550898,0.000535757,0.0003811845],"domain_scores_gemma":[0.9017629,0.08914954,0.003298315,0.002470023,0.002176508,0.001142728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0004733834,0.0002329748,0.005744713,0.0001988769,0.0003563347,0.0004097247,0.0005145597,0.4119833,0.001594529,0.5418814,0.003559367,0.03305063],"study_design_scores_gemma":[0.00006096376,0.00002617776,0.001088953,0.00002379558,0.00006500739,0.0000780274,0.00003004589,0.8338961,0.0001916305,0.1640289,0.0004640469,0.0000463185],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1732081,0.001834193,0.815891,0.00311639,0.00008372416,0.00007638156,0.0004031277,0.0002614755,0.005125754],"genre_scores_gemma":[0.904407,0.002336786,0.0820509,0.0004515966,0.000743393,0.0001373044,0.0005859346,0.0002153412,0.009071754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0183725,"threshold_uncertainty_score":0.09716427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03839871803933709,"score_gpt":0.2745720832587136,"score_spread":0.2361733652193765,"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."}}