{"id":"W2467978830","doi":"10.1177/0265813516656862","title":"Greenhouse gas emissions and urban form: Linking households’ socio-economic status with housing and transportation choices","year":2016,"lang":"en","type":"article","venue":"Environment and Planning B Urban Analytics and City Science","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Greenhouse gas; Urban sprawl; Census; Natural resource economics; Business; Population; Land use; Agricultural economics; Economic growth; Economics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005672724,0.000154962,0.0001765535,0.00007462149,0.001305577,0.0002452825,0.0001080217,0.00007010034,0.00002232811],"category_scores_gemma":[0.00001233744,0.0001101986,0.00001890053,0.00009604176,0.001849197,0.0007780929,0.00002270769,0.00009928269,4.36681e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006513903,"about_ca_system_score_gemma":0.00008044031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006027399,"about_ca_topic_score_gemma":0.000546371,"domain_scores_codex":[0.998637,0.00002094217,0.0001886174,0.0004814611,0.0002761208,0.0003958703],"domain_scores_gemma":[0.9993204,0.00009828943,0.0001220993,0.0001139676,0.000009397267,0.0003358033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000147826,0.00001336076,0.9887838,0.00001048541,0.000008339714,0.000003356778,0.007714373,0.000008594973,0.0002519786,0.0002182227,0.00001866922,0.002954054],"study_design_scores_gemma":[0.0004370746,0.00007955335,0.9929355,0.0001021142,0.00006182502,5.472927e-7,0.001672274,0.0003508469,0.00006930047,0.0006128708,0.003424807,0.000253239],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978946,0.0007318488,0.0006466292,0.0002729629,0.0000322173,0.0001257877,0.00002965483,0.00003148952,0.0002347655],"genre_scores_gemma":[0.9978074,0.001451808,0.0003438938,0.00004206026,0.00007675777,0.000002048167,0.000004156354,0.000008444727,0.0002634636],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006042098,"threshold_uncertainty_score":0.9999946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02492237691976775,"score_gpt":0.2527631921939364,"score_spread":0.2278408152741687,"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."}}