{"id":"W4387210621","doi":"10.59697/jik.v5i1.304","title":"IMPLEMENTASI DATA MINING PENGELOMPOKAN JENIS PENYAKIT PASIEN MENGGUNAKAN METODE CLUSTERING (STUDI KASUS : PUSKESMAS SAMBIREJO)","year":2021,"lang":"id","type":"article","venue":"Jurnal Informatika Kaputama (JIK)","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":"Medicine","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","insufficient_payload"],"consensus_categories":["open_science"],"category_scores_codex":[0.002964051,0.001094045,0.001216051,0.0005362921,0.002209203,0.003371354,0.006359292,0.0003379872,0.0005585528],"category_scores_gemma":[0.0007650765,0.001159945,0.0003500154,0.0018835,0.0002786806,0.005788846,0.009318966,0.001816199,0.001204789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003794457,"about_ca_system_score_gemma":0.001335542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007006855,"about_ca_topic_score_gemma":0.0005953594,"domain_scores_codex":[0.9913408,0.0005286675,0.002660553,0.001734496,0.001728059,0.002007406],"domain_scores_gemma":[0.9909359,0.0007323454,0.001568155,0.00529716,0.0005652927,0.0009011864],"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":[0.0001249134,0.0008800676,0.007346409,0.001113462,0.001913749,0.0006407961,0.05280007,0.003376641,0.0008161262,0.00295049,0.1999829,0.7280543],"study_design_scores_gemma":[0.002384555,0.0003426691,0.009116494,0.0005721444,0.0003970537,0.001437428,0.007429744,0.2739969,0.0006354983,0.00007115022,0.7019517,0.001664652],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2135854,0.006656576,0.4606669,0.0515852,0.01272333,0.004290415,0.006406188,0.003589708,0.2404963],"genre_scores_gemma":[0.8281431,0.0009298879,0.1504732,0.003666535,0.002290832,0.0002090884,0.006872637,0.0002363307,0.007178474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7263897,"threshold_uncertainty_score":0.9995729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06700875177334037,"score_gpt":0.3317793721214635,"score_spread":0.2647706203481232,"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."}}