{"id":"W4409604928","doi":"10.61091/jcmcc127b-330","title":"Design of Rule Extraction and Optimization Algorithms in Employee Performance Evaluation in Data Mining Environment","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"AI and HR Technologies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Data mining; Extraction (chemistry); Algorithm; Chemistry","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":[0.002770365,0.0001357456,0.0003792562,0.000499734,0.00008404293,0.0001113711,0.0002661037,0.0001094822,0.00000362484],"category_scores_gemma":[0.0004336977,0.0001303081,0.00001971812,0.0003337578,0.00004974637,0.0007350707,0.000330957,0.000206451,2.414557e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006506895,"about_ca_system_score_gemma":0.00005144439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001643674,"about_ca_topic_score_gemma":5.786147e-7,"domain_scores_codex":[0.9985309,0.00003332096,0.000783323,0.0001643288,0.0003446304,0.0001434967],"domain_scores_gemma":[0.998688,0.0002434907,0.0007279937,0.0001773692,0.000154977,0.000008163039],"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":[0.001062957,0.003613947,0.1055999,0.003410296,0.0003172862,0.00004031777,0.002459063,0.324223,0.002287758,0.2800888,0.000472599,0.2764241],"study_design_scores_gemma":[0.003241323,0.00007495431,0.003222415,0.0006599365,0.00007987188,0.000003846961,0.0005849609,0.9127977,0.0001294712,0.07902944,0.00004086158,0.0001351873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9582815,0.0003520523,0.03861971,0.0001031985,0.002112919,0.0003268692,3.158229e-7,0.00001409519,0.0001893685],"genre_scores_gemma":[0.9787638,0.0001354055,0.02085902,0.000008913804,0.0002167379,0.000002228121,0.000002887912,0.000009886411,0.000001109516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5885747,"threshold_uncertainty_score":0.5313811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03803127266384431,"score_gpt":0.2741304302159091,"score_spread":0.2360991575520648,"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."}}