{"id":"W3162142206","doi":"10.1021/acs.est.0c06671","title":"Greenhouse Gas Emission Mitigation Pathways for Urban Passenger Land Transport under Ambitious Climate Targets","year":2021,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto; National University of Singapore","keywords":"Greenhouse gas; Electrification; Climate change mitigation; Climate change; Public transport; Business; Natural resource economics; Modal shift; Environmental science; Software deployment; Electricity; Environmental planning; Environmental economics; Transport engineering; Engineering; Economics","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":[0.0004063013,0.0005474383,0.0003391532,0.0003098566,0.0004562363,0.0008260187,0.000582885,0.0008878443,0.002365737],"category_scores_gemma":[0.0006544914,0.0002593547,0.0006158004,0.0003869791,0.0004155233,0.0008643348,0.0007416914,0.0006207586,0.0001790473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001965477,"about_ca_system_score_gemma":0.002342233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06232762,"about_ca_topic_score_gemma":0.05345082,"domain_scores_codex":[0.9998512,0.00005441931,0.000004375044,0.00002667921,0.00001827105,0.00004495019],"domain_scores_gemma":[0.9998134,0.0000527808,0.00003447685,0.00001053223,0.00005118838,0.00003781391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002484683,0.00001933116,0.001840276,0.00001206243,0.000008331072,0.0000305459,0.00001988412,0.9925247,0.00045661,0.003918253,0.0002149772,0.0009301923],"study_design_scores_gemma":[0.00001900254,0.00005162914,0.001468776,0.000007865986,0.00001297098,0.000009100735,0.00008496927,0.9931329,0.000440646,0.003748644,0.001011094,0.00001253126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8919367,0.0001824596,0.06862859,0.001127475,0.00003613185,0.0001635236,0.00207172,0.0002445369,0.03560887],"genre_scores_gemma":[0.9927654,0.00008909076,0.004290914,0.00004362628,0.000002467882,0.00007058367,0.0003229943,0.0000195831,0.002395353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06232762,"threshold_uncertainty_score":0.1239297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005687065776309824,"score_gpt":0.1917339061836449,"score_spread":0.1860468404073351,"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."}}