{"id":"W3001615111","doi":"10.2139/ssrn.2962596","title":"Board Expertise and Executive Incentives","year":2017,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Corporate Finance and Governance","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Incentive; Executive compensation; Business; Executive summary; Executive functions; Accounting; Psychology; Corporate governance; Economics; Finance; Cognition; Neuroscience; Microeconomics","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":[0.004061794,0.0001696371,0.0003638909,0.001935822,0.001008764,0.003138803,0.0003843996,0.00198971,0.05198396],"category_scores_gemma":[0.03848338,0.0002062354,0.0001542336,0.0009205355,0.0009988782,0.002160395,0.001719413,0.001089095,0.002475027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009145545,"about_ca_system_score_gemma":0.001062048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001699844,"about_ca_topic_score_gemma":0.003992849,"domain_scores_codex":[0.9977469,0.0007673352,0.0001024555,0.0001947223,0.0003273548,0.0008613464],"domain_scores_gemma":[0.9358616,0.03649921,0.01205266,0.00144783,0.002898738,0.01123997],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001375829,0.00186884,0.6018668,0.0001883451,0.0002144779,0.00173281,0.003879788,0.004407906,0.002022528,0.2191294,0.03011186,0.1332013],"study_design_scores_gemma":[0.0006322899,0.0005579937,0.7236407,0.0002760217,0.0001622371,0.001145823,0.006822407,0.004658196,0.0008333605,0.2069998,0.05421046,0.00006055476],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7783041,0.00178028,0.002029692,0.008878598,0.0001250169,0.00003932759,0.0002301225,0.00004027412,0.2085727],"genre_scores_gemma":[0.9854501,0.0002100007,0.000117657,0.000344803,0.0001138733,0.000006708002,0.00005176699,0.000006659445,0.01369844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05198396,"threshold_uncertainty_score":0.1739037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113550299895204,"score_gpt":0.2218430508460384,"score_spread":0.2107075478470863,"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."}}