{"id":"W4404578742","doi":"10.62951/modem.v2i4.233","title":"Penerapan Algoritma K-Nearest Neighbor untuk Klasifikasi Usaha Masyarakat Berdasarkan Jenis Izin Usaha","year":2024,"lang":"en","type":"article","venue":"Modem","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","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004170876,0.0002758381,0.000241705,0.0001911118,0.0003382608,0.0008442069,0.001464396,0.0001119302,0.00008590058],"category_scores_gemma":[0.00004768903,0.000258717,0.000121334,0.0007998755,0.00007785577,0.000679167,0.00048161,0.0004624261,0.001527798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007088541,"about_ca_system_score_gemma":0.0001486164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004217577,"about_ca_topic_score_gemma":0.00004000362,"domain_scores_codex":[0.9977431,0.00009946804,0.0003121311,0.0009423223,0.000386046,0.0005169492],"domain_scores_gemma":[0.9982336,0.0001806111,0.00006010566,0.001250425,0.00005536179,0.0002199137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008471431,0.0002090307,0.001352733,0.0001197283,0.0001202097,0.0001309941,0.002483563,0.003010119,0.003549511,0.3175731,0.09060235,0.5808402],"study_design_scores_gemma":[0.0001669525,0.00007636088,0.001561167,0.00005111628,0.00002233895,0.0000579193,0.00002494648,0.6288141,0.0006494771,0.003561517,0.364664,0.0003501078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03344454,0.001690181,0.9306324,0.01191384,0.001238815,0.0003560231,0.0001170207,0.002123257,0.01848391],"genre_scores_gemma":[0.9025078,0.00007816913,0.08543549,0.0006377162,0.0004320728,0.0001375519,0.0001298254,0.00006126887,0.01058011],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8690633,"threshold_uncertainty_score":0.9999865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009817038144430183,"score_gpt":0.2595088432161351,"score_spread":0.2496918050717049,"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."}}