{"id":"W4384573875","doi":"10.59697/jsik.v6i2.189","title":"Data Mining Pengelompokan Pasien Rawat Inap Berdasarkan Kelas Bpjs Menggunakan Metode Clustering (Studi Kasus : Rumah Sakit Umum Daerah Dr. Rm. Djoelham Binjai)","year":2022,"lang":"id","type":"article","venue":"Jurnal Sistem Informasi Kaputama (JSIK)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":1,"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002908617,0.0006670369,0.0009474322,0.003465053,0.001470851,0.004932204,0.001025688,0.0009542402,0.006258732],"category_scores_gemma":[0.006759956,0.0004907067,0.0008349736,0.006530025,0.0007039986,0.003577548,0.00153377,0.001439589,0.005803696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001887317,"about_ca_system_score_gemma":0.002489692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008870844,"about_ca_topic_score_gemma":0.01297567,"domain_scores_codex":[0.9976151,0.0004377892,0.0001694502,0.0007026813,0.0009545526,0.0001203645],"domain_scores_gemma":[0.994951,0.002366892,0.0003030873,0.0003430016,0.001706154,0.0003299256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003609496,0.0001772117,0.02263059,0.001405832,0.0001656908,0.0004066785,0.00215695,0.005574598,0.009938979,0.0121211,0.08172885,0.8633325],"study_design_scores_gemma":[0.00006815283,0.0003292362,0.08263474,0.001370375,0.0003080597,0.001708167,0.009816155,0.06443182,0.03603469,0.0429796,0.7600505,0.0002685247],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2347529,0.0946256,0.3864452,0.08151058,0.003574879,0.001164871,0.01707409,0.007619594,0.1732323],"genre_scores_gemma":[0.5148375,0.0568611,0.2707477,0.003643073,0.001662414,0.0006597333,0.0154258,0.001287302,0.1348754],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008870844,"threshold_uncertainty_score":0.0209375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05099651351982436,"score_gpt":0.3015151187729321,"score_spread":0.2505186052531077,"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."}}