{"id":"W3199773792","doi":"10.2139/ssrn.3710491","title":"The Conduits of Price Discovery: A Machine Learning Approach","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Electrical conduit; Computer science; Telecommunications","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":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.02198452,0.0001581998,0.0003307382,0.000095853,0.0005336119,0.000328105,0.001407051,0.00005663402,0.00002946523],"category_scores_gemma":[0.0205428,0.00008719302,0.0002147003,0.001037551,0.0001355841,0.000339047,0.0002143446,0.002622623,0.000018165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000174391,"about_ca_system_score_gemma":0.001419025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001537494,"about_ca_topic_score_gemma":0.00002985199,"domain_scores_codex":[0.9945989,0.001360429,0.000749677,0.0003303853,0.001410045,0.001550552],"domain_scores_gemma":[0.9956034,0.002975674,0.0007691851,0.0002722289,0.0002480279,0.0001315158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009926264,0.0001076927,0.03040543,0.00001303976,0.0004257988,0.000006392554,0.002734149,0.003991881,0.003119927,0.267415,0.001103068,0.689685],"study_design_scores_gemma":[0.002578816,0.002280803,0.005010589,0.00003257324,0.0001120013,0.001420175,0.01499972,0.1023485,0.0008548087,0.7907466,0.07895291,0.0006625734],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2277912,0.007714597,0.7374747,0.004981033,0.0003451807,0.0002976024,0.000004531748,0.00005000105,0.02134108],"genre_scores_gemma":[0.9927752,0.000502491,0.001984154,0.0001091978,0.0002152458,0.000003187157,7.060285e-7,0.0000212504,0.00438859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.764984,"threshold_uncertainty_score":0.9996784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0735767431848387,"score_gpt":0.3509866965892209,"score_spread":0.2774099534043822,"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."}}