{"id":"W3199863058","doi":"10.33423/jabe.v22i10.3725","title":"3P Approach to Compensation Management and its Implications for Employee Performance at Work","year":2020,"lang":"en","type":"article","venue":"Journal of Applied Business and Economics","topic":"Banking, Crisis Management, COVID-19 Impact","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Compensation (psychology); Work (physics); Affect (linguistics); Business; Position (finance); Performance management; Risk analysis (engineering); Process management; Knowledge management; Computer science; Industrial organization; Marketing; Psychology; Engineering; Finance; Mechanical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001337462,0.0000935163,0.0001722193,0.00001926505,0.0001353545,0.0001008675,0.0001326153,0.0000305322,0.000006074364],"category_scores_gemma":[0.000006140091,0.00004640644,0.00002724818,0.0001605849,0.0000118393,0.00013869,0.0001148465,0.00003805004,0.000003239116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003638025,"about_ca_system_score_gemma":0.000003015974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001345814,"about_ca_topic_score_gemma":0.000003174624,"domain_scores_codex":[0.9994327,0.000003107894,0.0002393592,0.0001621496,0.00003378412,0.0001288686],"domain_scores_gemma":[0.9995841,0.00003044744,0.0002044548,0.00002925567,0.00004869105,0.0001030332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003049002,0.0003960295,0.1281601,0.001047832,0.0005068679,0.000001237164,0.001735536,0.02695139,0.01165159,0.04252826,0.02558202,0.7583901],"study_design_scores_gemma":[0.0003707999,0.00008713746,0.9595382,0.00001172653,0.00004353182,0.000003780467,0.0001330436,0.0006025805,0.00006519385,0.0004856968,0.03851003,0.0001482983],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9925346,0.0000422011,0.0003635117,0.005769306,0.00003315333,0.0003429043,0.000009165196,0.00000823648,0.0008968632],"genre_scores_gemma":[0.996266,0.0004006994,0.001511301,0.001587877,0.0001848602,0.00001766898,0.00001067516,0.000001742324,0.00001918246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8313781,"threshold_uncertainty_score":0.18924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05139794269083213,"score_gpt":0.2230116897169496,"score_spread":0.1716137470261174,"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."}}