{"id":"W4382240743","doi":"10.1007/978-981-19-7826-5_6","title":"The Importance of Compensation from Different Aspects: A Study of Akamai Inc.","year":2023,"lang":"en","type":"book-chapter","venue":"Applied economics and policy studies","topic":"Insurance and Financial Risk Management","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Compensation (psychology); Incentive; Agency (philosophy); Shareholder; Executive compensation; Work (physics); Business; Pay for performance; Public relations; Plan (archaeology); Finance; Engineering; Economics; Psychology; Political science; Sociology; Social psychology; Corporate governance; 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":[0.001012288,0.0003128934,0.0004655038,0.001847752,0.002566309,0.004582428,0.0006676847,0.001285822,0.01191864],"category_scores_gemma":[0.00336552,0.0003361447,0.0004265696,0.003258002,0.001258016,0.004331119,0.001069094,0.001642365,0.001363985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003349237,"about_ca_system_score_gemma":0.002686327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01604408,"about_ca_topic_score_gemma":0.02159499,"domain_scores_codex":[0.9994351,0.0001207648,0.00003274314,0.0000823632,0.0001791351,0.0001497682],"domain_scores_gemma":[0.9987043,0.0005964687,0.0001584127,0.0000712898,0.0003350559,0.0001343988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001421857,0.00006074262,0.01033405,0.0001286132,0.0000212416,0.0003426501,0.002415878,0.001229667,0.0002155429,0.8831344,0.02808452,0.07389056],"study_design_scores_gemma":[0.00003792453,0.0001140431,0.07314254,0.0006352136,0.0001707586,0.00112381,0.01023806,0.01008516,0.001160055,0.4546337,0.4485418,0.0001169289],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1845338,0.05696498,0.007514566,0.01430425,0.0006667184,0.00004314639,0.0004887511,0.0000865493,0.7353973],"genre_scores_gemma":[0.8672126,0.01269014,0.002154851,0.0005894952,0.0001805243,0.00003800349,0.000169846,0.00005599214,0.1169086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01604408,"threshold_uncertainty_score":0.03987181,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05179388238633229,"score_gpt":0.2495175909090473,"score_spread":0.197723708522715,"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."}}