{"id":"W4399974175","doi":"10.33772/anoatik.v2i1.30","title":"PENERAPAN METODE NAIVE BAYES UNTUK KLASIFIKASI KATEGORI OLAH PANGAN (STUDI KASUS DINAS KESEHATAN KOTA PALEMBANG)","year":2024,"lang":"id","type":"article","venue":"AnoaTIK Jurnal Teknologi Informasi dan Komputer","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Crosslight Software (Canada)","funders":"","keywords":"Statistics; Mathematics; Psychology","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":[0.009598389,0.001463006,0.001846879,0.00316554,0.001971273,0.007141149,0.001490875,0.001713636,0.01396247],"category_scores_gemma":[0.02489405,0.0008471213,0.001902507,0.003544758,0.0009819074,0.00438725,0.001479859,0.002384457,0.006298127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003394594,"about_ca_system_score_gemma":0.006271973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04641216,"about_ca_topic_score_gemma":0.05416404,"domain_scores_codex":[0.9933862,0.002345501,0.0006785739,0.00139194,0.001717617,0.0004801912],"domain_scores_gemma":[0.9891376,0.006526704,0.0005200825,0.0005218001,0.003021035,0.0002727135],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007565557,0.0003239661,0.136701,0.00353152,0.0008499617,0.0009005577,0.007449859,0.00790767,0.004458924,0.0162449,0.0273635,0.7935116],"study_design_scores_gemma":[0.0004603678,0.001120026,0.2587871,0.008453134,0.004196689,0.003579317,0.04087665,0.1469347,0.01884039,0.1203958,0.3954624,0.0008934222],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.339304,0.03412863,0.446548,0.02435968,0.00330567,0.004140261,0.01257196,0.004115376,0.1315263],"genre_scores_gemma":[0.6912295,0.009833851,0.2372853,0.0024455,0.000435966,0.001709859,0.005746364,0.0004574273,0.05085614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04641216,"threshold_uncertainty_score":0.09228402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01979618669687207,"score_gpt":0.2763024918371026,"score_spread":0.2565063051402305,"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."}}