{"id":"W3122985308","doi":"","title":"Trading Volume and Stock Investments","year":2009,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Market liquidity; Stock (firearms); Algorithmic trading; Proxy (statistics); Financial economics; Business; Stock trading; Monetary economics; Inventory turnover; Economics; Volume (thermodynamics); Market capitalization; Econometrics; Stock exchange; Finance; Stock market; Mathematics; Geography","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":[0.0007537823,0.0002360554,0.0002715354,0.00162124,0.0002055524,0.002138637,0.0002960949,0.0005643064,0.007860923],"category_scores_gemma":[0.01126221,0.0001309449,0.0002595259,0.002062384,0.0003158471,0.001340139,0.0005699926,0.0007123241,0.001167588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004644967,"about_ca_system_score_gemma":0.0001959751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001841652,"about_ca_topic_score_gemma":0.001647453,"domain_scores_codex":[0.9993817,0.0001572287,0.00007313137,0.00008931995,0.0002242319,0.00007442861],"domain_scores_gemma":[0.9854094,0.006391112,0.006071799,0.0003475773,0.0006087061,0.001171361],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002238321,0.0001493477,0.964092,0.00007065538,0.0002608453,0.0002320265,0.0002225316,0.002524845,0.0004285447,0.006562583,0.0009744125,0.02425846],"study_design_scores_gemma":[0.00001545472,0.0001407589,0.9787932,0.00005831672,0.0000611725,0.0004304636,0.0002120916,0.003728768,0.0002891427,0.0117213,0.004526295,0.00002300128],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9574446,0.005870321,0.001390339,0.000817947,0.00005332036,0.00002289222,0.001745379,0.00005368861,0.03260156],"genre_scores_gemma":[0.9941437,0.001183981,0.0002396527,0.00005104412,0.0001069617,0.00000983157,0.0009276441,0.00000898362,0.00332817],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007860923,"threshold_uncertainty_score":0.02629745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01773967468499611,"score_gpt":0.2079876130501342,"score_spread":0.1902479383651381,"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."}}