{"id":"W2183150602","doi":"10.1111/peps.12141","title":"Using a Computational Model to Understand Possible Sources of Skews in Distributions of Job Performance","year":2015,"lang":"en","type":"article","venue":"Personnel Psychology","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Luck; Multiplicative function; Monte Carlo method; Psychology; Econometrics; Job performance; Statistical physics; Social psychology; Statistics; Mathematics; Epistemology; Job satisfaction","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":[0.004737183,0.0005703521,0.0007810601,0.001040152,0.0005642567,0.002588344,0.001748753,0.001254707,0.005682013],"category_scores_gemma":[0.03011962,0.0004775478,0.001014893,0.000934576,0.001614748,0.004146114,0.001335778,0.001779482,0.0005851207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002187663,"about_ca_system_score_gemma":0.001540506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005519603,"about_ca_topic_score_gemma":0.004094083,"domain_scores_codex":[0.9983225,0.0008900195,0.00005468086,0.0003251888,0.0002517669,0.0001558282],"domain_scores_gemma":[0.98127,0.01470032,0.001627272,0.001604311,0.0005843225,0.0002138812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001749472,0.0001960804,0.009512093,0.00006115533,0.00007069013,0.0001263679,0.000588168,0.6761537,0.001345848,0.2978273,0.0007304308,0.01321318],"study_design_scores_gemma":[0.0000254032,0.0000463925,0.001822372,0.000009768351,0.000009728829,0.00006472437,0.00007054662,0.9189826,0.0001939254,0.07824781,0.0005057186,0.0000210657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2514883,0.00008737625,0.7312441,0.001759957,0.00006327521,0.0001620692,0.0003000898,0.0002701402,0.01462462],"genre_scores_gemma":[0.9333683,0.0001155633,0.06213202,0.0002517985,0.00004302024,0.0003161617,0.0002144253,0.00005253045,0.003506244],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005682013,"threshold_uncertainty_score":0.02505291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.277971483531097,"score_gpt":0.4477881120403012,"score_spread":0.1698166285092042,"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."}}