{"id":"W2006442201","doi":"10.1016/j.atmosenv.2008.05.008","title":"Use of MODIS products to simplify and evaluate a forest fire plume dispersion model for PM10 exposure assessment","year":2008,"lang":"en","type":"article","venue":"Atmospheric Environment","topic":"Fire effects on ecosystems","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia; University of British Columbia","funders":"Ministry of Forests, Lands and Natural Resource Operations; National Oceanic and Atmospheric Administration; Michael Smith Health Research BC; British Columbia Lung Association","keywords":"Moderate-resolution imaging spectroradiometer; Environmental science; Plume; Atmospheric dispersion modeling; Meteorology; Remote sensing; Aerosol; Smoke; Atmospheric sciences; Pixel; Terrain; Dispersion (optics); Air pollution; Satellite; Geography; Geology; Cartography","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002926549,0.0002939309,0.0003442058,0.000003415895,0.0001861387,0.00001725446,0.0002023414,0.00009229338,0.0001438666],"category_scores_gemma":[0.00005395708,0.0002615346,0.00007752141,0.0001255931,0.0001735774,0.0002979244,0.0003329591,0.00009193733,0.00007115141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004283689,"about_ca_system_score_gemma":0.00001883671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004560897,"about_ca_topic_score_gemma":0.00004021726,"domain_scores_codex":[0.9978333,0.00006889654,0.000382598,0.0007074839,0.0005901721,0.0004175376],"domain_scores_gemma":[0.9988968,0.00009803579,0.0001611063,0.0006216805,0.000007333007,0.0002150284],"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":[0.00009259203,0.0004016003,0.2886668,0.00009437851,0.00004355257,0.000007825327,0.00114678,0.6788377,0.01459777,0.00001324129,0.00390309,0.01219463],"study_design_scores_gemma":[0.0004853971,0.0005420969,0.2487254,0.00002266776,0.00003635136,0.000009665494,0.00002412922,0.7458513,0.0002829856,0.00002747678,0.003726522,0.0002659754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9776726,0.00009845816,0.01955953,0.000419658,0.00007093506,0.002064527,0.00003145854,0.00002936681,0.00005342257],"genre_scores_gemma":[0.9171371,0.0001466343,0.0808178,0.0001559067,0.00002389879,0.0003667417,0.0000143795,0.00004699353,0.001290494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06701358,"threshold_uncertainty_score":0.9999837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02334682477501866,"score_gpt":0.2299911362522922,"score_spread":0.2066443114772735,"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."}}