{"id":"W3123941123","doi":"","title":"Liquidity and Market Efficiency: A Large Sample Study","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Market liquidity; Tick size; Predictability; Business; Sample (material); Market capitalization; Order (exchange); Monetary economics; Market maker; Financial economics; Econometrics; Economics; Finance; Stock market","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":[0.003970446,0.0004382841,0.0007053528,0.001184399,0.0007701306,0.0007749917,0.0005764941,0.0006627603,0.003263118],"category_scores_gemma":[0.01555057,0.0003571129,0.0007452065,0.00104402,0.0006391159,0.0009418318,0.001045753,0.0008488238,0.0005596277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002322083,"about_ca_system_score_gemma":0.0002843425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002518245,"about_ca_topic_score_gemma":0.002815502,"domain_scores_codex":[0.997346,0.001567501,0.0001637516,0.0004439059,0.0003063834,0.0001723928],"domain_scores_gemma":[0.9852977,0.00905522,0.001916606,0.002331933,0.0005749859,0.0008235241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001144605,0.001101629,0.9805948,0.00004014302,0.001114588,0.0006701158,0.0006981521,0.0003053426,0.001046011,0.0002841433,0.001051054,0.01194943],"study_design_scores_gemma":[0.0002176459,0.00160679,0.9916561,0.00001245487,0.0003897096,0.001108334,0.0005665823,0.002571075,0.0003909214,0.0002797517,0.001168255,0.00003240097],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985782,0.000162353,0.0006519058,0.00004121079,0.000003574814,0.0000399094,0.0002874875,0.000007836587,0.0002276327],"genre_scores_gemma":[0.9986143,0.00007676103,0.0004731801,0.00003952231,0.00002578475,0.00003622053,0.0005397499,0.000006020008,0.0001883175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003970446,"threshold_uncertainty_score":0.02099794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362615914092585,"score_gpt":0.222491273587152,"score_spread":0.2088651144462262,"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."}}