{"id":"W4383503615","doi":"10.2139/ssrn.4493166","title":"Can AI Read the Minds of Corporate Executives?","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University; McGill University; Montreal Police Service; University of Guelph","funders":"","keywords":"Business; Management; Psychology; Accounting; Economics","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":[0.003584859,0.0003038931,0.0003150861,0.001101949,0.00194691,0.00773391,0.0006762068,0.00316781,0.01782317],"category_scores_gemma":[0.0322279,0.0001883629,0.000249267,0.001019437,0.004599023,0.009855405,0.001501444,0.006271359,0.003995651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001559596,"about_ca_system_score_gemma":0.001662763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005058038,"about_ca_topic_score_gemma":0.006355344,"domain_scores_codex":[0.9980421,0.0009818437,0.00005340977,0.0001697375,0.0003705899,0.0003823063],"domain_scores_gemma":[0.9830378,0.008500451,0.00165482,0.0007805419,0.003066274,0.00296002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004799719,0.0002687741,0.0330401,0.0004735042,0.0001492764,0.0009710941,0.03569915,0.0006345002,0.00139965,0.2365258,0.4526354,0.2377228],"study_design_scores_gemma":[0.00006579194,0.000146998,0.0183235,0.0008731183,0.00006325804,0.0005252955,0.05181328,0.001030144,0.0007900359,0.3069943,0.6192878,0.00008650242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04180151,0.01159649,0.002559037,0.7093653,0.00783395,0.00001390499,0.0001514105,0.0001051061,0.2265732],"genre_scores_gemma":[0.7410426,0.01368457,0.001733164,0.159762,0.008441767,0.00002775426,0.0001203652,0.0001314758,0.07505628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01782317,"threshold_uncertainty_score":0.05962443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03129997330657601,"score_gpt":0.2213270711088743,"score_spread":0.1900270978022983,"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."}}