{"id":"W2140160830","doi":"10.5267/j.msl.2012.02.012","title":"CEO emotional bias and investment decision, Bayesian network method","year":2012,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Customer churn and segmentation","field":"Business, Management and Accounting","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bayesian network; Bayesian probability; Investment (military); Psychology; Econometrics; Computer science; Investment decisions; Statistics; Artificial intelligence; Business; Economics; Mathematics; Finance; Behavioral economics; Political science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002993745,0.0005001139,0.0004988411,0.001647342,0.0003615544,0.0008333371,0.000581697,0.0007129483,0.003055082],"category_scores_gemma":[0.01648875,0.0002666825,0.0003605885,0.001200561,0.0004029884,0.001309584,0.0004792623,0.0006601026,0.0002659647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008637119,"about_ca_system_score_gemma":0.0005385921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005024691,"about_ca_topic_score_gemma":0.003720199,"domain_scores_codex":[0.9984266,0.001081744,0.00005932192,0.0001843406,0.0001613546,0.0000866831],"domain_scores_gemma":[0.9935039,0.00537925,0.0005885183,0.0001459177,0.0002632986,0.0001191488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001739367,0.001246739,0.2289685,0.000374821,0.0005800055,0.0005273611,0.001330524,0.4039975,0.002872596,0.07950959,0.003416194,0.2754368],"study_design_scores_gemma":[0.00005169342,0.0001237738,0.02115578,0.00004651434,0.00007672349,0.0001103473,0.0001866755,0.9425252,0.0005076728,0.03410115,0.001072829,0.00004168989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5522376,0.0007119193,0.437925,0.0008591305,0.00007512413,0.0003240624,0.0006658121,0.000187404,0.007013996],"genre_scores_gemma":[0.939843,0.000406994,0.05717694,0.00007468453,0.00005421443,0.0002204802,0.0004671486,0.0000130672,0.001743405],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005024691,"threshold_uncertainty_score":0.01583266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02741503400903809,"score_gpt":0.266601307388149,"score_spread":0.2391862733791109,"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."}}