{"id":"W4402380092","doi":"10.62951/bridge.v2i4.199","title":"Pengelompokan Data Kasus Keracunan Makanan Biologis Berdasarkan Faktor Penyebab Menggunakan Metode Clustering","year":2024,"lang":"en","type":"article","venue":"Bridge","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":"Cluster analysis; Mathematics; Computer science; Statistics","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"],"consensus_categories":[],"category_scores_codex":[0.0008656274,0.0002756679,0.0002543337,0.0002100033,0.0003096926,0.0008325066,0.003533465,0.00008739733,0.00003953643],"category_scores_gemma":[0.0001471866,0.0002495144,0.00007772614,0.0006282093,0.00007322177,0.0008743184,0.002494803,0.0004141142,0.0007709991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006000297,"about_ca_system_score_gemma":0.0001355591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007861735,"about_ca_topic_score_gemma":0.0001355463,"domain_scores_codex":[0.9974645,0.0001307669,0.0003533776,0.001263485,0.0002775854,0.0005102222],"domain_scores_gemma":[0.9966551,0.0002315279,0.00008228209,0.002805354,0.00003928268,0.0001864405],"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":[0.00001073532,0.0001352198,0.0006380011,0.0001525576,0.0002069455,0.0001778967,0.001734365,0.0001994965,0.002518396,0.05291485,0.2004195,0.7408921],"study_design_scores_gemma":[0.0001899033,0.00007157838,0.009248578,0.00007917904,0.00003923581,0.0001336993,0.00004140694,0.2650281,0.0001374654,0.0003802108,0.7242178,0.000432922],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02192775,0.002480349,0.9243842,0.01608732,0.002348129,0.0006545591,0.0009596532,0.003916607,0.0272414],"genre_scores_gemma":[0.9394865,0.00008107666,0.05673709,0.000410743,0.0005083453,0.0000555154,0.0009387765,0.00004500496,0.001736949],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9175587,"threshold_uncertainty_score":0.9999957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.084808803073497,"score_gpt":0.3475543587852378,"score_spread":0.2627455557117407,"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."}}