{"id":"W4406219072","doi":"10.2139/ssrn.5089390","title":"Application of Large Vision Models for Daily Wildfire Risk Mapping Using Remote Sensing and Meteorological Data","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Remote sensing; Environmental science; Computer science; Meteorology; Geography","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":[0.000760567,0.0005736746,0.0005676143,0.0006519327,0.0003906778,0.001223723,0.0006099051,0.0007890535,0.001830654],"category_scores_gemma":[0.002811671,0.0005042112,0.000696227,0.0006057815,0.0002137823,0.00114081,0.0005720883,0.0007060344,0.0003267783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008924477,"about_ca_system_score_gemma":0.000839856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03011936,"about_ca_topic_score_gemma":0.02332703,"domain_scores_codex":[0.999824,0.00004227424,0.000009001667,0.0000674515,0.00003365014,0.00002358906],"domain_scores_gemma":[0.9991906,0.0004961661,0.00005160755,0.00009813849,0.0001223225,0.00004120733],"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":[0.0001088905,0.0001533693,0.003188893,0.00003396511,0.0001014801,0.00006067526,0.00003310697,0.9060337,0.003224466,0.001591731,0.001605624,0.08386411],"study_design_scores_gemma":[0.000004301183,0.000005155024,0.0004016821,0.000001005328,0.000003741782,0.000004357174,0.000002658965,0.9987643,0.0002240081,0.0005039964,0.00008215453,0.000002676542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4495278,0.0008024959,0.5394925,0.0007422051,0.0002580208,0.0001092086,0.000946515,0.003131671,0.004989751],"genre_scores_gemma":[0.9389285,0.0001676044,0.05863053,0.00006709802,0.00004138621,0.00004893912,0.0005545839,0.0001370843,0.001424134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03011936,"threshold_uncertainty_score":0.05988806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917084410220882,"score_gpt":0.2822636191901923,"score_spread":0.2630927750879835,"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."}}