{"id":"W2989613929","doi":"10.14203/oseana.2018.vol.43no.2.16","title":"KARAKTERISTIK DAN DAMPAK SIKLON TROPIS YANG TUMBUH DI SEKITAR WILAYAH INDONESIA","year":2018,"lang":"en","type":"article","venue":"OSEANA","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"WiLAN (Canada)","funders":"","keywords":"Tropical cyclone; Cyclone (programming language); Extratropical cyclone; Climatology; Environmental science; Equator; Tropical cyclone scales; Latitude; Geography; Geology","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":[0.0002470865,0.0005242967,0.0005066318,0.0009978942,0.000463322,0.00168116,0.0002492972,0.0003267961,0.007512934],"category_scores_gemma":[0.0007248623,0.0002887876,0.0004591426,0.0007977289,0.0005722002,0.0005285935,0.0005999797,0.0005573449,0.001154494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003800405,"about_ca_system_score_gemma":0.0004400189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005700727,"about_ca_topic_score_gemma":0.00439548,"domain_scores_codex":[0.9998094,0.00002712014,0.00002034147,0.00004190295,0.00006014216,0.00004094328],"domain_scores_gemma":[0.9996626,0.00006701618,0.0001063688,0.00002295216,0.00009050666,0.00005056833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002224548,0.000448301,0.6046399,0.001781935,0.000497158,0.02367962,0.00433463,0.009980983,0.1094779,0.00281548,0.01017872,0.2299409],"study_design_scores_gemma":[0.00003423628,0.0001578798,0.9582236,0.0001803734,0.0001712449,0.01359147,0.003642353,0.005382682,0.005554959,0.002022695,0.01095616,0.00008234612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.966902,0.005752867,0.004577643,0.0007757987,0.0001117745,0.00008926157,0.002401994,0.0001957109,0.01919293],"genre_scores_gemma":[0.9933129,0.002062505,0.001084815,0.00005530901,0.00003040457,0.0000296804,0.0005876558,0.00003790187,0.002798834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007512934,"threshold_uncertainty_score":0.02513325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01028718361609056,"score_gpt":0.2599549192476049,"score_spread":0.2496677356315143,"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."}}