{"id":"W4410722191","doi":"10.20473/adj.v9i1.41364","title":"ANALYSIS OF CIVIL SERVANT HUMAN RESOURCES DEVELOPMENT BASED ON COMPETENCE","year":2025,"lang":"en","type":"article","venue":"Airlangga Development Journal","topic":"Employee Performance and Management","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Civil servant; Competence (human resources); Human resources; Business; Management; Political science; Law; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00104126,0.000222713,0.0001462984,0.002929278,0.0005242407,0.001266912,0.0002396944,0.0001734596,0.00330501],"category_scores_gemma":[0.004787357,0.00006409997,0.0003491079,0.001645484,0.0006703049,0.0007999113,0.001130627,0.0004272943,0.0003537627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002368856,"about_ca_system_score_gemma":0.002478565,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01305889,"about_ca_topic_score_gemma":0.011607,"domain_scores_codex":[0.9990649,0.0002381621,0.00005543625,0.00006327903,0.0003704531,0.0002079174],"domain_scores_gemma":[0.9966915,0.001218809,0.0004868739,0.000097594,0.000909448,0.0005958555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001003895,0.0002822863,0.8539952,0.0001716295,0.00006760104,0.0005604138,0.01189043,0.0036666,0.001570422,0.02606331,0.001848572,0.09978317],"study_design_scores_gemma":[0.000005620557,0.0001094622,0.9661925,0.0001249373,0.00002358111,0.0001709509,0.0147086,0.008102522,0.0008610642,0.003001724,0.006677846,0.00002123625],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9372754,0.0002188379,0.003162333,0.0003369857,0.000009466061,0.0000992728,0.0002360527,0.00001752971,0.05864403],"genre_scores_gemma":[0.9980909,0.00006388457,0.000607512,0.000009273293,0.000001862796,0.00002179946,0.00008897646,0.000001802102,0.001113939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01305889,"threshold_uncertainty_score":0.02596575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256667725427454,"score_gpt":0.3052101521380828,"score_spread":0.2826434748838083,"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."}}