{"id":"W2318673026","doi":"10.5194/acpd-14-12235-2014","title":"Aerosol-CFD modelling of ultrafine and black carbon particle emission, dilution, and growth near roadways","year":2014,"lang":"en","type":"article","venue":"","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Environment and Climate Change Canada","funders":"Natural Resources Canada","keywords":"Aerosol; Ultrafine particle; Particle number; Nucleation; Particle (ecology); Turbulence; Dilution; Atmospheric sciences; Environmental science; Turbulence kinetic energy; Mechanics; Meteorology; Computational fluid dynamics; Atmospheric dispersion modeling; Chemistry; Materials science; Air pollution; Physics; Thermodynamics; Nanotechnology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002043658,0.0006044155,0.0005355502,0.0004259284,0.0005527228,0.0009481107,0.0006685669,0.001336208,0.000972531],"category_scores_gemma":[0.0004959064,0.0002675305,0.0007741259,0.0003218959,0.0004369596,0.0004645404,0.0004767467,0.0004850245,0.0001630405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00129736,"about_ca_system_score_gemma":0.001061866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04232052,"about_ca_topic_score_gemma":0.01663169,"domain_scores_codex":[0.9998591,0.00002546817,0.000007486194,0.00003618166,0.00003605497,0.00003569478],"domain_scores_gemma":[0.9997501,0.0001227611,0.0000300338,0.00001320165,0.00005763094,0.00002625402],"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":[0.00003843058,0.00004635749,0.004239122,0.00001926403,0.00001552654,0.00009297499,0.00002052739,0.9898706,0.003612847,0.0004202476,0.00007196161,0.001552155],"study_design_scores_gemma":[0.000003752216,0.00001293892,0.0008577604,0.000001271056,0.000002414894,0.000005733752,0.000007455699,0.9983764,0.0005989432,0.00005399217,0.00007575605,0.000003467834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9716876,0.0001674604,0.02140529,0.00009645404,0.00003540936,0.00005255149,0.0004406066,0.0001656914,0.005949046],"genre_scores_gemma":[0.9951362,0.00005900176,0.003447848,0.00001145467,0.000005169262,0.00002233527,0.0001594365,0.00001201522,0.001146568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04232052,"threshold_uncertainty_score":0.08414835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03396975446546285,"score_gpt":0.2484640280465139,"score_spread":0.2144942735810511,"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."}}