{"id":"W6887770014","doi":"10.17632/ccn43vxdjg.1","title":"Information Sharing in Financial Markets","year":2024,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Information sharing; Financial market; Information system; Information asymmetry; Key (lock); Financial analysis","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":[0.001366352,0.00152288,0.0009530236,0.003747839,0.0009417296,0.002210465,0.002150012,0.001916937,0.08842791],"category_scores_gemma":[0.008604542,0.0004994446,0.001385396,0.006488709,0.0004451851,0.001449993,0.001769513,0.001488843,0.0658006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001442409,"about_ca_system_score_gemma":0.001775789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01947276,"about_ca_topic_score_gemma":0.03768868,"domain_scores_codex":[0.9988142,0.0002721674,0.0001353006,0.0002667752,0.0003021031,0.0002095231],"domain_scores_gemma":[0.9964958,0.001359854,0.0003072858,0.0008706576,0.0006708552,0.0002955468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008475529,0.00005540489,0.001913988,0.0004216856,0.00002691614,0.00001701224,0.00002722264,0.0006326014,0.0000548288,0.0008434926,0.991738,0.004184159],"study_design_scores_gemma":[0.0007186036,0.00008863459,0.01699566,0.0005432422,0.00006616782,0.0001373184,0.0003870981,0.003484243,0.000913626,0.00762435,0.9689686,0.00007249421],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006359092,0.00005957363,0.0001224481,0.0001339866,0.00002582964,0.00001869747,0.997629,0.0004041517,0.0009703988],"genre_scores_gemma":[0.001809965,0.00007177066,0.0007410129,0.00007466206,0.00001140581,0.0001389294,0.9959288,0.00007184222,0.001151545],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08842791,"threshold_uncertainty_score":0.2958208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04431511567638452,"score_gpt":0.3408691621060885,"score_spread":0.296554046429704,"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."}}