{"id":"W4385577341","doi":"10.1109/accai58221.2023.10201125","title":"Artificial Intelligence enabled Employee Performance Prediction using Comprehensive Learning Metrics","year":2023,"lang":"en","type":"article","venue":"","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Human capital; Machine learning; Recall; Knowledge management; Artificial intelligence; Trait; Precision and recall; Data science; Psychology; Cognitive psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001899456,0.0001320848,0.0001452369,0.0007491271,0.0004052291,0.000227203,0.0001937394,0.00009058863,0.0001498672],"category_scores_gemma":[0.0001913585,0.0001196272,0.0000453284,0.002434488,0.00005961656,0.0009576503,0.0002789719,0.0002100273,0.0008938812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002937997,"about_ca_system_score_gemma":0.00001006388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001223541,"about_ca_topic_score_gemma":0.000008357178,"domain_scores_codex":[0.9989895,0.000004662483,0.0002467496,0.0002306561,0.0002217093,0.0003067801],"domain_scores_gemma":[0.9995273,0.00005120437,0.0001052141,0.0001412339,0.0001689937,0.000006021945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000810239,0.00007695514,0.518778,0.000526092,0.00009133099,0.00003292683,0.0001742871,0.107617,0.00899778,0.04970339,0.004684568,0.3092366],"study_design_scores_gemma":[0.0000563776,0.00003016768,0.02421716,0.00004514579,0.00004535228,0.000001919593,0.003219153,0.9473426,0.003278486,0.005921177,0.01555162,0.0002908316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981943,0.00002737579,0.01076324,0.000157278,0.0003837631,0.0001481997,5.207656e-7,0.002124944,0.004451666],"genre_scores_gemma":[0.9984447,0.00006817443,0.0004614321,0.0001432432,0.0004309239,0.00000790371,0.00001881881,0.00002033946,0.0004044127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8397256,"threshold_uncertainty_score":0.999884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.101597383738803,"score_gpt":0.2732218611052542,"score_spread":0.1716244773664511,"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."}}