{"id":"W4386389382","doi":"10.14569/ijacsa.2023.0140836","title":"Model Classification of Fire Weather Index using the SVM-FF Method on Forest Fire in North Sumatra, Indonesia","year":2023,"lang":"en","type":"article","venue":"International Journal of Advanced Computer Science and Applications","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Support vector machine; Outlier; Computer science; Index (typography); Environmental science; Meteorology; Machine learning; Artificial intelligence; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006711368,0.00008330773,0.0001153689,0.0001427547,0.0001165577,0.00004839792,0.0007537674,0.00002469286,0.000003016965],"category_scores_gemma":[0.00002273364,0.00006123531,0.00003624065,0.0009036508,0.0002095566,0.000453412,0.0001412638,0.000130125,0.000006810954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001739379,"about_ca_system_score_gemma":0.00005788638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000506843,"about_ca_topic_score_gemma":0.00009656904,"domain_scores_codex":[0.9986054,0.0000318064,0.0003420457,0.0001996425,0.0006861545,0.0001349317],"domain_scores_gemma":[0.999161,0.000145143,0.0003286049,0.000183066,0.0001296836,0.00005248945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001586716,0.00006518752,0.06147027,0.000003736897,0.000007179575,0.000002100049,0.000337498,0.7165508,0.006229084,0.000688834,0.00003954138,0.2145899],"study_design_scores_gemma":[0.0001606159,0.00002706774,0.281712,0.00002551549,0.000002267648,0.00001787696,0.00004019618,0.7169963,0.0001521556,0.0006480357,0.0001720747,0.00004594066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7955536,0.00001084232,0.2035462,0.0005427772,0.00009764133,0.0001865621,0.000004497432,0.00000738277,0.00005047732],"genre_scores_gemma":[0.9900915,0.00002644755,0.009682069,0.0000998386,0.00006281402,0.00002159888,0.000001297047,0.000006082315,0.00000833126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2202417,"threshold_uncertainty_score":0.2497104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173014941341837,"score_gpt":0.3025897138147376,"score_spread":0.2808595644013193,"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."}}