{"id":"W2801632056","doi":"","title":"Examining the Impact of Smoke Aerosol on Clouds and Precipitation using a Regional Model WRF-Chem-SMOKE and A-Train Data: A Case Study of Canadian Boreal Forest Wildfires in Summer 2007","year":2010,"lang":"en","type":"article","venue":"13th Conference on Cloud Physics/13th Conference on Atmospheric Radiation (28 June–2 July 2010)","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Smoke; Environmental science; Precipitation; Weather Research and Forecasting Model; Aerosol; Taiga; Climatology; Boreal; Meteorology; Atmospheric sciences; Forestry; Geography; Geology","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":[0.001267422,0.001003849,0.0005226214,0.0005566654,0.001585058,0.001116545,0.001702756,0.001209649,0.000691417],"category_scores_gemma":[0.002003323,0.000559032,0.0008969436,0.001026882,0.0007577441,0.0007561806,0.0004728195,0.0008115755,0.0001215588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008353858,"about_ca_system_score_gemma":0.005276734,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.938024,"about_ca_topic_score_gemma":0.9509326,"domain_scores_codex":[0.9996247,0.00006343737,0.0000180019,0.00008068499,0.00009990489,0.0001132324],"domain_scores_gemma":[0.9987546,0.0004908317,0.0000966174,0.00008583476,0.0004230051,0.0001490819],"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":[0.001538511,0.001415699,0.4648006,0.0001452331,0.0006710825,0.001557202,0.0006143793,0.4940553,0.01603289,0.0009146519,0.00313845,0.01511604],"study_design_scores_gemma":[0.0002540699,0.0002703448,0.3277898,0.0000135125,0.0002611324,0.0001205446,0.001088597,0.6615598,0.007175189,0.0002363503,0.001126278,0.0001044806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985461,0.00003780948,0.0001651382,0.00009530099,0.000006783303,0.00001838472,0.0006068267,0.0000479841,0.0004757057],"genre_scores_gemma":[0.9976664,0.00004571845,0.0009771915,0.00002273542,0.000004368066,0.000005419901,0.001002337,0.00001640655,0.0002595574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06197602,"threshold_uncertainty_score":0.1246819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1345175410648725,"score_gpt":0.309316350741133,"score_spread":0.1747988096762605,"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."}}