{"id":"W3093493289","doi":"10.1016/j.trd.2020.102585","title":"Marginal emission factors for public transit: Effects of urban scale and density","year":2020,"lang":"en","type":"article","venue":"Transportation Research Part D Transport and Environment","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Public transport; Transit (satellite); Scale (ratio); Mode (computer interface); Population; Geography; Environmental science; Transport engineering; Demography; Engineering; Cartography; Computer science; Sociology","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":[0.0005051948,0.0003420415,0.000348903,0.0004219605,0.0002687769,0.0008139811,0.0003551086,0.0002644886,0.005242523],"category_scores_gemma":[0.001764855,0.000253958,0.0009074926,0.0005999091,0.000402604,0.001053131,0.0004329553,0.0002814954,0.0003620628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008483907,"about_ca_system_score_gemma":0.0007066925,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02833138,"about_ca_topic_score_gemma":0.02868403,"domain_scores_codex":[0.9997314,0.00007769833,0.000009477888,0.00004362332,0.00004241226,0.00009535635],"domain_scores_gemma":[0.9986566,0.0008403398,0.00008805047,0.0001057838,0.0002261141,0.00008306676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009471168,0.0007637747,0.460191,0.000456878,0.0008938773,0.001118642,0.00110708,0.3843724,0.0491338,0.04098266,0.002966629,0.04854209],"study_design_scores_gemma":[0.00009977721,0.0008497158,0.8454678,0.00003749011,0.0005365022,0.0004778239,0.001946423,0.1173972,0.01885516,0.00980719,0.004404261,0.0001207079],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9904813,0.0002528744,0.003672707,0.0000709782,0.000007438072,0.00001002874,0.0006606596,0.00005498995,0.004789076],"genre_scores_gemma":[0.9986855,0.00004799016,0.0002199524,0.000003434387,0.000002625047,0.000004559641,0.0001894012,0.0000171016,0.0008294337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02833138,"threshold_uncertainty_score":0.05633295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03570207560138898,"score_gpt":0.248548676531221,"score_spread":0.212846600929832,"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."}}