{"id":"W4401894700","doi":"10.3390/f15091493","title":"Predicting Forest Fire Area Growth Rate Using an Ensemble Algorithm","year":2024,"lang":"en","type":"article","venue":"Forests","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Terrain; Random forest; Hyperparameter; Collinearity; Computer science; Algorithm; Environmental science; Statistics; Geography; Mathematics; Cartography; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001502381,0.0009874696,0.001418526,0.001243133,0.0004545069,0.000700138,0.001020226,0.0007862689,0.0006896947],"category_scores_gemma":[0.001734856,0.0004062279,0.001223803,0.001107531,0.0001847569,0.0008511064,0.0005734458,0.001019318,0.0002256197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000456809,"about_ca_system_score_gemma":0.0007814618,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01564416,"about_ca_topic_score_gemma":0.0108175,"domain_scores_codex":[0.9996006,0.000092537,0.00003171654,0.0001092478,0.00009366585,0.00007229755],"domain_scores_gemma":[0.9994345,0.0002479983,0.00006176479,0.00004546465,0.0001744325,0.00003590053],"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":[0.0000833615,0.00008620969,0.008974407,0.00002430353,0.0001367522,0.00005356763,0.00003465982,0.8787719,0.001089645,0.0004721165,0.0008973547,0.1093757],"study_design_scores_gemma":[0.000001470953,0.000005406265,0.0003589827,0.000001468266,0.000006637129,0.00000368072,0.000002239108,0.9993532,0.00009374275,0.0001215342,0.00004980763,0.000001811672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2976864,0.001506775,0.6964357,0.0002516008,0.0001700806,0.00007798652,0.0003635254,0.00120417,0.002303829],"genre_scores_gemma":[0.9261153,0.0004835474,0.07119722,0.00006866857,0.00009282541,0.00007833885,0.0006377391,0.00003868022,0.001287629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01564416,"threshold_uncertainty_score":0.03110623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01348768201559407,"score_gpt":0.2338670824462029,"score_spread":0.2203794004306088,"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."}}