{"id":"W4401636466","doi":"10.51544/jurnalmi.v5i1.1197","title":"PENERAPAN DATA MINING KORELASI UMUR, PANGKAT DAN PENDIDIKAN TERHADAP JABATAN PADA POLRES BINJAI MENGGUNAKAN METODE ALGORITMA APRIORI","year":2020,"lang":"id","type":"article","venue":"JURNAL MAHAJANA INFORMASI","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Computer science; Mathematics","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":["metaepi_narrow","sts","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.001396962,0.001107715,0.001094945,0.0004258064,0.001531611,0.002373597,0.008736252,0.0003765625,0.0001173513],"category_scores_gemma":[0.000673253,0.001090037,0.0003274905,0.001822735,0.0003313535,0.005225442,0.005337832,0.002013499,0.000480533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001774962,"about_ca_system_score_gemma":0.0009214078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004512087,"about_ca_topic_score_gemma":0.0001200792,"domain_scores_codex":[0.9924165,0.0003218213,0.001913324,0.001939763,0.001654926,0.00175369],"domain_scores_gemma":[0.9924713,0.0004100157,0.001251973,0.004021805,0.0002536165,0.001591227],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000267147,0.0007657232,0.01080592,0.0006508642,0.001302612,0.000405053,0.03228731,0.0007779385,0.002294834,0.02804999,0.1398525,0.7825401],"study_design_scores_gemma":[0.001457122,0.0008311676,0.006016127,0.000208904,0.0002861469,0.0002483169,0.002639219,0.2021484,0.0006892143,0.00003092313,0.7840812,0.001363314],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2265209,0.01060634,0.3456702,0.1754199,0.01325519,0.006797312,0.003928053,0.006943047,0.210859],"genre_scores_gemma":[0.8484957,0.001119468,0.1213568,0.01022478,0.00411965,0.0001169986,0.005688917,0.0003038594,0.00857389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7811768,"threshold_uncertainty_score":0.9997683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05993675724750001,"score_gpt":0.2953231961000846,"score_spread":0.2353864388525846,"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."}}