{"id":"W3186825587","doi":"10.1155/2021/3881254","title":"Simulating the Principal‐Agent Relationship between Enterprise Owners and Professional Managers Using Evolutionary Game Theory and System Dynamics","year":2021,"lang":"en","type":"article","venue":"Complexity","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"China Three Gorges University","keywords":"Principal (computer security); Incentive; Standardization; Evolutionary game theory; Principal–agent problem; Business; Game theory; Microeconomics; Industrial organization; Knowledge management; Computer science; Economics; Finance; Corporate governance","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0007199279,0.00009102734,0.00013903,0.0000241525,0.001419009,0.00006373685,0.00009491184,0.00004970597,0.000009343224],"category_scores_gemma":[0.0001718714,0.00007636284,0.00003518998,0.00009319003,0.0007070227,0.0001337107,0.0003387347,0.0001360976,0.000002327218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005292071,"about_ca_system_score_gemma":0.00007634716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003076431,"about_ca_topic_score_gemma":0.0003095774,"domain_scores_codex":[0.9987326,0.0005325788,0.0001914299,0.0002175232,0.0001421131,0.0001838015],"domain_scores_gemma":[0.9989988,0.0006649016,0.00009800253,0.0001243171,0.0000424852,0.00007151579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007617058,0.00001221505,0.7139051,0.00002264136,0.00001555454,0.000002787481,0.007043816,0.00004729626,0.00001116578,0.278686,0.000007103931,0.0002386526],"study_design_scores_gemma":[0.0002389523,0.000009019949,0.8646109,0.0001337824,0.00004660202,0.00000427724,0.1015478,0.01042842,0.000007855953,0.02262148,0.000163718,0.000187192],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948339,0.000600473,0.0003794929,0.0004766986,0.000201481,0.0002395609,0.00002622356,0.00004113315,0.003201023],"genre_scores_gemma":[0.9985731,0.000008726357,0.0009859507,0.00003856533,0.00006984446,0.000008633417,0.00001288146,0.00000767448,0.0002946822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2560646,"threshold_uncertainty_score":0.999881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1383276911007638,"score_gpt":0.3841580459031445,"score_spread":0.2458303548023806,"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."}}