{"id":"W2994231404","doi":"10.30865/komik.v3i1.1675","title":"PEMANFAATAN DATAMINING PADA PENGELOMPOKAN PROVINSI TERHADAP PENCEMARAN LINGKUNGAN HIDUP","year":2019,"lang":"en","type":"article","venue":"KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation Cluster (Canada)","funders":"","keywords":"Pollution; Geography; Java; Environmental pollution; Environmental protection; Ecology; Computer science; Biology","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":[0.0009227348,0.0005632835,0.0005188209,0.002425249,0.0008261214,0.002048603,0.0004834463,0.000346445,0.007439395],"category_scores_gemma":[0.002334338,0.0002830985,0.0004731901,0.004697966,0.0003239475,0.0009985631,0.0007434917,0.0006154751,0.00178087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009083919,"about_ca_system_score_gemma":0.002571444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01790693,"about_ca_topic_score_gemma":0.02191104,"domain_scores_codex":[0.9992207,0.0001382229,0.00009611499,0.0002107479,0.0002509734,0.00008316759],"domain_scores_gemma":[0.9986339,0.0003677994,0.0001653477,0.0001445987,0.0005918439,0.00009641088],"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":[0.0007611529,0.0005781861,0.1814436,0.002373934,0.0002945182,0.001791312,0.006033614,0.01072415,0.009849107,0.005954396,0.03173381,0.7484622],"study_design_scores_gemma":[0.0001605944,0.0005858669,0.4695297,0.0008241296,0.0004074375,0.001444436,0.02930729,0.04492388,0.03493131,0.007763237,0.409862,0.0002600682],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8213262,0.003768213,0.06046303,0.002376491,0.0006503448,0.001091078,0.04828602,0.002081592,0.05995696],"genre_scores_gemma":[0.8519083,0.00260833,0.07601156,0.0002318973,0.0001055876,0.001019913,0.03974205,0.0002713269,0.02810099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01790693,"threshold_uncertainty_score":0.03560543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01530618588813311,"score_gpt":0.2430882416775816,"score_spread":0.2277820557894485,"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."}}