{"id":"W3152697490","doi":"","title":"JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI JUMLAH PASIEN RAWAT JALAN BAGI PENGGUNA NARKOBA MENGGUNAKAN METODE BACKPROPAGATION (STUDI KASUS : KANTOR BNN KOTA BINJAI)","year":2020,"lang":"id","type":"article","venue":"","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":"Mathematics","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":[0.001572104,0.001309885,0.0009605835,0.0005908112,0.001003412,0.003232985,0.001130664,0.001412712,0.01334418],"category_scores_gemma":[0.004394178,0.0005811036,0.0008964445,0.0007388439,0.0006823234,0.003732427,0.001332485,0.002380564,0.004982535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001480845,"about_ca_system_score_gemma":0.002269224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01102251,"about_ca_topic_score_gemma":0.01574383,"domain_scores_codex":[0.9991795,0.0001409206,0.00006223732,0.0002062197,0.0003080902,0.0001029054],"domain_scores_gemma":[0.9981433,0.0007148434,0.0001358287,0.0001532859,0.0007532106,0.00009948986],"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":[0.001604267,0.0006324318,0.01640772,0.001659243,0.0004033568,0.0006246338,0.001395943,0.03572726,0.05558708,0.01198394,0.01811957,0.8558546],"study_design_scores_gemma":[0.0003913104,0.002393497,0.07534382,0.001522459,0.001554212,0.002177797,0.00514839,0.4917872,0.1763369,0.04764514,0.1951909,0.0005083937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4091789,0.009904679,0.4442452,0.008933567,0.001711953,0.000762428,0.002131357,0.004245599,0.1188863],"genre_scores_gemma":[0.7463441,0.006922023,0.15349,0.001576017,0.0002015823,0.0003574987,0.001634804,0.0006269088,0.08884715],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01334418,"threshold_uncertainty_score":0.04464078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03420725686816811,"score_gpt":0.2583673266524203,"score_spread":0.2241600697842522,"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."}}