{"id":"W4402574215","doi":"10.1287/mnsc.2022.02659","title":"The Use and Usefulness of Big Data in Finance: Evidence from Financial Analysts","year":2024,"lang":"en","type":"article","venue":"Management Science","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Big data; Economics; Finance; Business; Computer science","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":[0.04091229,0.0003311624,0.0002339281,0.004888112,0.001080865,0.005750961,0.0008714562,0.001696608,0.001514956],"category_scores_gemma":[0.2690354,0.0004222901,0.0003446851,0.0065319,0.002855327,0.007967296,0.002766255,0.001982765,0.0004094281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146337,"about_ca_system_score_gemma":0.00145188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005985372,"about_ca_topic_score_gemma":0.006480249,"domain_scores_codex":[0.9712919,0.01442577,0.002050841,0.001574252,0.0101162,0.0005410811],"domain_scores_gemma":[0.4015661,0.4667265,0.07692596,0.02100461,0.02955115,0.00422571],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006712318,0.0001440454,0.77061,0.0008412881,0.0004102772,0.0003724523,0.01905348,0.001148903,0.0005108235,0.01358163,0.01924365,0.1734123],"study_design_scores_gemma":[0.0001497847,0.0003759189,0.7790481,0.004476355,0.0004380747,0.001203306,0.03312953,0.0127255,0.002912946,0.04236038,0.1228303,0.0003498823],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8604998,0.02426899,0.008504887,0.06124061,0.0004790871,0.0001122337,0.002943419,0.0001102072,0.0418409],"genre_scores_gemma":[0.9870105,0.006017975,0.00346024,0.001785941,0.0004535889,0.00003246494,0.0007248268,0.00003909534,0.000475304],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04091229,"threshold_uncertainty_score":0.2163674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1750730164652896,"score_gpt":0.26616917736046,"score_spread":0.09109616089517039,"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."}}