{"id":"W4384573886","doi":"10.59697/jsik.v6i2.169","title":"PENERAPAN DATA MINING PENGELOMPOKAN DATA PASIEN BERDASRKAN JENIS PENYAKIT MENGGUNAKAN METODE CLUSTERING (STUDI KASUS KLINIK MITRA ND)","year":2022,"lang":"id","type":"article","venue":"Jurnal Sistem Informasi Kaputama (JSIK)","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":"Humanities; Art","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","research_integrity"],"consensus_categories":["metaepi_narrow","open_science"],"category_scores_codex":[0.006792596,0.001370514,0.001529474,0.0007753322,0.005551835,0.002951286,0.02231596,0.00031075,0.0003629599],"category_scores_gemma":[0.0006299494,0.001498424,0.0003910572,0.002322795,0.0003439822,0.00581034,0.03171477,0.00318271,0.0003119127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005938187,"about_ca_system_score_gemma":0.001418567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006874729,"about_ca_topic_score_gemma":0.0004739486,"domain_scores_codex":[0.9874248,0.0009555542,0.003018775,0.00328931,0.002946677,0.002364885],"domain_scores_gemma":[0.98383,0.000953773,0.002289182,0.01153262,0.0003127371,0.001081726],"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":[0.0005227058,0.002106813,0.01019938,0.001156526,0.002870307,0.0006823024,0.03752123,0.01778075,0.0006516774,0.003927476,0.1731093,0.7494715],"study_design_scores_gemma":[0.00172057,0.0005518653,0.003783887,0.0001735452,0.0003884769,0.0009124469,0.00296176,0.2998862,0.00003607037,0.00001620812,0.688178,0.001390942],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.271477,0.02024098,0.1820872,0.07154097,0.03576298,0.01385608,0.02324363,0.00877885,0.3730123],"genre_scores_gemma":[0.9064959,0.0003431631,0.05050522,0.002401644,0.00267918,0.000382947,0.01652482,0.0003238594,0.02034331],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7480806,"threshold_uncertainty_score":0.9999046,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08241776119678437,"score_gpt":0.3159980042057383,"score_spread":0.2335802430089539,"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."}}