{"id":"W2598122296","doi":"10.1088/1748-9326/aa59ba","title":"More connected urban roads reduce US GHG emissions","year":2017,"lang":"en","type":"article","venue":"Environmental Research Letters","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Urban sprawl; Greenhouse gas; Environmental science; Land use; Environmental planning; Business; Environmental resource management; Natural resource economics; Transport engineering; Civil engineering; Economics; Engineering","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":[0.0003674209,0.0004270892,0.0001157443,0.0007265318,0.0002926248,0.001268392,0.0003142824,0.0005335413,0.007283773],"category_scores_gemma":[0.001876494,0.000135734,0.0006134,0.001391367,0.0004478216,0.001565293,0.00113357,0.0003695264,0.0005582942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125786,"about_ca_system_score_gemma":0.0006997662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01502301,"about_ca_topic_score_gemma":0.03487876,"domain_scores_codex":[0.9996841,0.00007950407,0.00001055796,0.00006442028,0.00008452452,0.00007689487],"domain_scores_gemma":[0.9994919,0.0001166289,0.0001366563,0.00007278832,0.0001338089,0.00004814401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002566695,0.000417596,0.3842515,0.000476369,0.0006920507,0.0003610562,0.0005157885,0.3680793,0.006815096,0.09172034,0.01388424,0.1325301],"study_design_scores_gemma":[0.00009450015,0.0005530593,0.5380793,0.000334844,0.000645022,0.0004887448,0.002697318,0.1892354,0.01417785,0.1168939,0.1367041,0.00009605672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9228012,0.0006690495,0.01577938,0.002104033,0.00005854396,0.00007010224,0.005962056,0.000308152,0.05224745],"genre_scores_gemma":[0.9939761,0.0002880458,0.003077952,0.00009709726,0.00001049462,0.00002087353,0.00107688,0.00002173975,0.001430874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01502301,"threshold_uncertainty_score":0.02987111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06528225751119661,"score_gpt":0.3937545096166191,"score_spread":0.3284722521054225,"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."}}