{"id":"W2938203099","doi":"10.5194/amt-12-5247-2019","title":"Traffic-related air pollution near roadways: discerning local impacts from background","year":2019,"lang":"en","type":"article","venue":"Atmospheric measurement techniques","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of the Environment, Conservation and Parks; Environment and Climate Change Canada; University of Toronto","funders":"Environment and Climate Change Canada","keywords":"Environmental science; Pollutant; Air pollution; Air quality index; Particulates; Pollution; Meteorology; Ultrafine particle; Atmospheric sciences; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0005214633,0.000360227,0.0004607429,0.0009996664,0.0004664366,0.001257547,0.0004138967,0.0003482699,0.0003308223],"category_scores_gemma":[0.001588707,0.0001859085,0.0002041436,0.001524636,0.0003472935,0.0003122795,0.0003944756,0.0002489765,0.0001411614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001332946,"about_ca_system_score_gemma":0.00149034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4017206,"about_ca_topic_score_gemma":0.6605151,"domain_scores_codex":[0.9994988,0.00005924641,0.0000228412,0.0001428486,0.0002176559,0.00005844832],"domain_scores_gemma":[0.9991454,0.0001365274,0.0001401048,0.00005771568,0.0004720645,0.00004828252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001630425,0.0000302585,0.9635889,0.0001776069,0.0001353553,0.0001292931,0.0003634486,0.003933868,0.01016557,0.00007750661,0.0003180897,0.02091707],"study_design_scores_gemma":[0.000002218347,0.00002229451,0.9928485,0.00001385464,0.00003588126,0.00004048786,0.0002860291,0.004454293,0.001866751,0.00003230449,0.000388628,0.000008689007],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949831,0.0004742413,0.002362751,0.00002227665,0.000008207215,0.00002349565,0.0006420445,0.00003916997,0.001444782],"genre_scores_gemma":[0.997479,0.0001565319,0.001546398,0.000009893809,0.000004985981,0.00001034678,0.0005186433,0.000006112939,0.0002680151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4017206,"threshold_uncertainty_score":0.7987646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03379566180767395,"score_gpt":0.2633764320853563,"score_spread":0.2295807702776824,"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."}}