{"id":"W4402642778","doi":"10.1007/s10661-024-13104-0","title":"Dynamic patterns of particulate matter concentration and size distribution in urban street canyons: insights into diurnal and short-term seasonal variations","year":2024,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Wind and Air Flow Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Particulates; Environmental science; Canyon; Term (time); Street canyon; Ecotoxicology; Atmospheric sciences; Hydrology (agriculture); Geography; Ecology; Geology; Environmental chemistry; Chemistry; Cartography; Geotechnical engineering","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":[0.0001472587,0.0001313166,0.0002479465,0.0008101275,0.0002474883,0.0004274075,0.0002166583,0.0002760452,0.0008182676],"category_scores_gemma":[0.0003223213,0.0001796897,0.0001668929,0.001061337,0.000245191,0.0002637393,0.0002877438,0.0001576177,0.0001927737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002732073,"about_ca_system_score_gemma":0.0002209303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.013754,"about_ca_topic_score_gemma":0.03548947,"domain_scores_codex":[0.9999158,0.0000123952,0.000005284673,0.00002944452,0.00001604539,0.00002096797],"domain_scores_gemma":[0.9997233,0.00006826608,0.00006697309,0.00001771614,0.00007038936,0.00005337931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004089133,0.00006416904,0.9741895,0.00004199669,0.00008759742,0.0001629749,0.0007129983,0.0006204682,0.01461618,0.0001204712,0.0003690343,0.008605706],"study_design_scores_gemma":[0.000001205927,0.00001626167,0.9992454,0.00000156833,0.000005237603,0.00002480825,0.0001994565,0.0003186023,0.00009186053,0.0000144228,0.00007942008,0.000001852211],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993217,0.00006770477,0.00009798836,0.00001079778,0.000001684772,0.000003128059,0.0002393665,0.000005345757,0.0002523349],"genre_scores_gemma":[0.9992068,0.00005706958,0.0001232763,0.000005576731,0.00000392591,0.000005614529,0.0003602929,0.000003376126,0.0002340214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.013754,"threshold_uncertainty_score":0.02734792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005429401760243943,"score_gpt":0.2415440225026235,"score_spread":0.2361146207423795,"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."}}