{"id":"W4400445696","doi":"10.5465/amproc.2024.21608abstract","title":"Artificial Intelligence and Corporate Investment Decisions","year":2024,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Stock Market Forecasting Methods","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Business; Investment decisions; Investment (military); Finance; Political science; Behavioral 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":[0.001826052,0.0001400529,0.0001658625,0.0009869274,0.000510746,0.002604648,0.000212791,0.0007938161,0.00430734],"category_scores_gemma":[0.009311838,0.00009517519,0.0001331305,0.001302424,0.0009763504,0.0009862798,0.0005609374,0.0007457308,0.0003343146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001303395,"about_ca_system_score_gemma":0.0006439725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003145847,"about_ca_topic_score_gemma":0.00580647,"domain_scores_codex":[0.9987527,0.0006542116,0.00007213859,0.0001021626,0.000166058,0.0002526366],"domain_scores_gemma":[0.9856716,0.007397155,0.004843062,0.00025542,0.0005510104,0.001281876],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001893994,0.000420047,0.8647437,0.00006597772,0.0001501829,0.0005968887,0.00188952,0.009777895,0.0003633104,0.05693508,0.002744612,0.06212325],"study_design_scores_gemma":[0.00004782438,0.00021602,0.8711683,0.0001326147,0.00006730324,0.0003442375,0.005828389,0.02106717,0.0005676803,0.08432309,0.01618719,0.00005025698],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9635996,0.0007579365,0.0008589336,0.003543867,0.00001366523,0.00002521738,0.00007909211,0.000006140378,0.03111553],"genre_scores_gemma":[0.9982657,0.0002233154,0.0001537515,0.0001027254,0.00001227591,0.000004450179,0.00003380992,9.979466e-7,0.001203034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00430734,"threshold_uncertainty_score":0.01440948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3287005713161469,"score_gpt":0.425076848588332,"score_spread":0.09637627727218506,"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."}}