{"id":"W4213149274","doi":"10.31219/osf.io/2gwrb","title":"IMPLEMENTASI METODE K-MEANS CLUSTERING DALAM PENGELOMPOKAN PENYEBARAN COVID-19 DI SURABAYA","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada); WiLAN (Canada)","funders":"","keywords":"Silhouette; Cluster analysis; Coronavirus disease 2019 (COVID-19); Cluster (spacecraft); Corona (planetary geology); Geography; Index (typography); Computer science; Data mining; Cartography; Artificial intelligence; Physics; Medicine; World Wide Web","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","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001595393,0.0005245526,0.0005256779,0.000349221,0.0009601552,0.0008290907,0.005150435,0.0001420764,0.001144341],"category_scores_gemma":[0.0002174024,0.0005469577,0.0002609701,0.0004469134,0.00006618546,0.0002886167,0.01377372,0.001500491,0.00009791765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004487397,"about_ca_system_score_gemma":0.000767812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003842538,"about_ca_topic_score_gemma":0.0008067734,"domain_scores_codex":[0.9957349,0.0004201631,0.0006801334,0.001772923,0.0007142698,0.0006775596],"domain_scores_gemma":[0.9953845,0.0003958891,0.0004026922,0.003246815,0.00005822906,0.0005119029],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005873489,0.001203431,0.03666859,0.001707861,0.001197712,0.0003174869,0.02514324,0.2647736,0.0006245089,0.2745196,0.1624834,0.2313018],"study_design_scores_gemma":[0.0007394319,0.000114744,0.004623452,0.00002862962,0.00008552622,0.00009203872,0.0006798368,0.3200451,0.00003649257,0.002794199,0.6694478,0.001312734],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002249074,0.0001098048,0.9641125,0.01023916,0.0009284557,0.0007737317,0.0003345785,0.001633168,0.01961959],"genre_scores_gemma":[0.6162726,0.0001939411,0.3597923,0.004849993,0.0004158235,0.002045411,0.005718635,0.0001620647,0.01054933],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6140235,"threshold_uncertainty_score":0.9997687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05365274174165455,"score_gpt":0.360491461063218,"score_spread":0.3068387193215635,"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."}}