{"id":"W2260068654","doi":"10.1016/j.scitotenv.2016.01.030","title":"Operational and environmental determinants of in-vehicle CO and PM2.5 exposure","year":2016,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"American University of Beirut","keywords":"Environmental science; Pollutant; Robustness (evolution); Multivariate statistics; Air pollutants; Air quality index; Vehicle type; Air pollution; Environmental engineering; Meteorology; Engineering; Transport engineering; Statistics; Mathematics; Geography; Chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007872127,0.0003087399,0.0001998726,0.0006170748,0.0004139571,0.001403747,0.0007071212,0.000788978,0.003215599],"category_scores_gemma":[0.003649571,0.0003149798,0.0006908637,0.0009265622,0.0005700437,0.0006394669,0.0008773102,0.0006805255,0.0004005387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006552247,"about_ca_system_score_gemma":0.0008777965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06537834,"about_ca_topic_score_gemma":0.04444351,"domain_scores_codex":[0.9990706,0.0002913799,0.00006449782,0.0001358532,0.0001261741,0.000311555],"domain_scores_gemma":[0.9952453,0.001517759,0.001376745,0.0002964994,0.0005444939,0.001019281],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001436398,0.0001258922,0.9979445,0.000006286382,0.00005523505,0.00004798584,0.0001178324,0.0001874874,0.0002587816,0.0001065539,0.00008103587,0.0009248274],"study_design_scores_gemma":[0.000001212201,0.00004845941,0.9989153,0.000003218396,0.00002009174,0.00002956493,0.0003999698,0.0003204565,0.00006853564,0.00005432106,0.0001360428,0.000002920473],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983914,0.0001638092,0.0001214922,0.0001071902,0.000007962522,0.000007845357,0.0003720341,0.000003927326,0.0008241915],"genre_scores_gemma":[0.9993358,0.00005655138,0.00003699492,0.000009553599,0.000009992435,0.000003139945,0.0002057287,0.00000293627,0.0003393397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06537834,"threshold_uncertainty_score":0.1299956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01889763131360587,"score_gpt":0.2570328455921577,"score_spread":0.2381352142785518,"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."}}