{"id":"W4220802620","doi":"10.3390/su14073881","title":"Wildfire Risk Forecasting Using Weights of Evidence and Statistical Index Models","year":2022,"lang":"en","type":"article","venue":"Sustainability","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Aeronautics and Space Administration","keywords":"Land cover; Statistics; Receiver operating characteristic; Environmental science; Altitude (triangle); Index (typography); Physical geography; Geography; Mathematics; Land use; Computer science; Engineering; Civil engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001700702,0.0001179441,0.0001998801,0.00003117424,0.0003705854,0.00001470101,0.0001773657,0.0000328963,0.0002210787],"category_scores_gemma":[0.001327497,0.0001024011,0.00003363928,0.0002554349,0.0003076712,0.0003462681,0.0006748654,0.0002228885,8.795774e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001405681,"about_ca_system_score_gemma":0.00008260141,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01322487,"about_ca_topic_score_gemma":0.0001151153,"domain_scores_codex":[0.9980091,0.0005610414,0.0002840077,0.0004038037,0.0004434139,0.0002985631],"domain_scores_gemma":[0.9987446,0.0006563385,0.0001621382,0.0003197983,0.00002470725,0.00009241387],"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":[0.00006476491,0.00008341833,0.9461261,0.0001566638,0.000006194416,0.00001790465,0.0009373279,0.03328573,0.00005148906,0.0002819333,0.00003016954,0.01895828],"study_design_scores_gemma":[0.0001286143,0.0001284952,0.1762444,0.000011343,0.00001434677,0.00001604229,0.0004709438,0.7819932,0.00002002853,0.04077106,0.00008710272,0.0001144675],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857398,0.00007321101,0.01338186,0.00006023203,0.00005706971,0.0005600445,0.0000268837,0.00002239745,0.0000785032],"genre_scores_gemma":[0.9982702,0.000002029843,0.001634608,0.000009957267,0.00001007471,0.00003269274,0.000001087958,0.0000113101,0.00002808318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7698817,"threshold_uncertainty_score":0.9933462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04171434710034942,"score_gpt":0.2728304445764953,"score_spread":0.2311160974761459,"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."}}