{"id":"W4401642763","doi":"10.22495/cocv21i3editorial","title":"Editorial: Artificial intelligence and corporate governance — Opportunities and challenges","year":2024,"lang":"en","type":"editorial","venue":"Corporate Ownership and Control","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Corporate governance; Emerging markets; China; Business; Accountability; Accounting; Audit; Agency (philosophy); Principal–agent problem; Political science; Finance; Sociology","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":[0.007664097,0.003202906,0.004242043,0.005543016,0.004373713,0.01349196,0.003282696,0.01251463,0.01975707],"category_scores_gemma":[0.03352564,0.0009061452,0.002183797,0.002965783,0.003193061,0.006026097,0.001856365,0.01557791,0.01362714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003212058,"about_ca_system_score_gemma":0.003942539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001554252,"about_ca_topic_score_gemma":0.003963595,"domain_scores_codex":[0.9926844,0.00136692,0.0007342257,0.0008275837,0.003978864,0.000407946],"domain_scores_gemma":[0.9597267,0.01932235,0.001881263,0.0008718224,0.01392435,0.004273611],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001691377,0.000009272021,0.00001469925,0.0000925426,0.000007468603,0.00003144465,0.000009334766,0.00002187514,0.00002054349,0.000352969,0.9967889,0.002634049],"study_design_scores_gemma":[0.00005890042,0.00002501623,0.000276762,0.0006541808,0.00003380225,0.0001231218,0.00006181713,0.0002568024,0.00007262391,0.003281449,0.9951347,0.00002084084],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00002431611,0.003102655,0.00008626856,0.03875048,0.9565166,0.00001155662,0.00004472315,0.00003129438,0.001431972],"genre_scores_gemma":[0.0002964279,0.002428993,0.00007870078,0.01170655,0.9787526,0.00001576113,0.00002862579,0.00003675751,0.006655478],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01975707,"threshold_uncertainty_score":0.06609398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1252599619209467,"score_gpt":0.2306376181285804,"score_spread":0.1053776562076337,"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."}}