{"id":"W613788211","doi":"","title":"Quantifying the Effects of Land-use and Socio-economics on the Generation of Traffic Emissions and Individual Exposure to Air Pollution","year":2013,"lang":"en","type":"article","venue":"Transportation Research Board 92nd Annual MeetingTransportation Research Board","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Air pollution; Environmental science; Pollution; Land use; Proxy (statistics); Car ownership; Transport engineering; Geography; Engineering; Statistics; Public transport; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002161578,0.0002122695,0.0002748554,0.0004326871,0.0006427728,0.0001079738,0.000277063,0.0001681207,0.00003767984],"category_scores_gemma":[0.0002978472,0.0001469011,0.00007257606,0.0007147052,0.0004252817,0.0004844534,0.00001179155,0.0007518742,0.000006452269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000385875,"about_ca_system_score_gemma":0.00009361561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009885853,"about_ca_topic_score_gemma":0.001212038,"domain_scores_codex":[0.9971287,0.0003897922,0.0006293564,0.00034943,0.0009615251,0.0005411553],"domain_scores_gemma":[0.9969717,0.001590951,0.00008581419,0.0003120039,0.0007852684,0.000254246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007033619,0.000503241,0.1679611,0.00386335,0.0005554285,0.00001792357,0.1015363,0.4055459,0.2324502,0.008725774,0.02079241,0.05734498],"study_design_scores_gemma":[0.0007779304,0.0007351422,0.9620417,0.0004502932,0.00003208767,4.120418e-7,0.006464958,0.01130621,0.01652875,0.00009983998,0.001311773,0.0002508821],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949009,0.0002902772,0.00007537391,0.00297279,0.00007715482,0.001421761,0.0001773954,0.00005209417,0.00003224357],"genre_scores_gemma":[0.9978234,0.001213302,0.0003659518,0.00006967776,0.00007634667,0.0002755704,0.0000724144,0.0000409356,0.0000623938],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7940807,"threshold_uncertainty_score":0.5990454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07393125545474166,"score_gpt":0.3191706093579201,"score_spread":0.2452393539031785,"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."}}