{"id":"W4378977854","doi":"10.1021/acs.est.2c06993","title":"Personal Mobility Choices and Disparities in Carbon Emissions","year":2023,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Greenhouse gas; Equity (law); Environmental justice; Air pollution; Natural resource economics; Land use; Environmental science; Population; Business; Geography; Environmental engineering; Economics; Environmental health; Engineering; Political science","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":[0.0003898194,0.0001502714,0.0001477934,0.0004984912,0.0006689273,0.0005841271,0.000233409,0.0003003004,0.00253495],"category_scores_gemma":[0.001674459,0.00009728492,0.0002639566,0.0008345474,0.0004836794,0.0003748953,0.0007431417,0.0002887589,0.00008979307],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284719,"about_ca_system_score_gemma":0.0008074078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2391229,"about_ca_topic_score_gemma":0.407392,"domain_scores_codex":[0.9997359,0.00005292691,0.00001731654,0.00005882156,0.000058979,0.00007611067],"domain_scores_gemma":[0.9993999,0.0001196536,0.0002102071,0.00005335319,0.0000844739,0.0001325157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002197595,0.00002822879,0.9944907,0.00001632053,0.00005934468,0.00005067009,0.001067345,0.0002454438,0.000141127,0.0004766917,0.0001531538,0.003249033],"study_design_scores_gemma":[9.077172e-7,0.000007589402,0.9983911,0.00001002158,0.000009862771,0.00002316504,0.0007674826,0.0002243763,0.00003780693,0.0001625976,0.0003617802,0.000003280908],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979441,0.0001979886,0.0001372945,0.0001535734,0.000004233738,0.000005729542,0.0002941962,0.000001575055,0.001261294],"genre_scores_gemma":[0.9996663,0.0000542979,0.00003460603,0.000008158893,0.000001693638,0.000001716899,0.00006818535,6.19182e-7,0.0001642798],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2391229,"threshold_uncertainty_score":0.4754621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0114299589648063,"score_gpt":0.2705181595454934,"score_spread":0.259088200580687,"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."}}