{"id":"W2624984233","doi":"10.1177/0042098017708985","title":"Telecommuting and sustainable travel: Reduction of overall travel time, increases in non-motorised travel and congestion relief?","year":2017,"lang":"en","type":"article","venue":"Urban Studies","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":157,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Telecommuting; Travel time; Travel behavior; TRIPS architecture; Transport engineering; Business; Traffic congestion; Work (physics); Journey to work; Travel survey; Demographic economics; Economics; Engineering; Public transport","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":[],"consensus_categories":[],"category_scores_codex":[0.001074927,0.0001370631,0.0003791601,0.00008416828,0.001052157,0.00008168016,0.0001450073,0.00009189651,0.000009660323],"category_scores_gemma":[0.0005263088,0.000129835,0.00003607992,0.00008868497,0.0008697496,0.000491776,0.00005904855,0.0001264478,5.353302e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007626259,"about_ca_system_score_gemma":0.00006427402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01337655,"about_ca_topic_score_gemma":0.001778513,"domain_scores_codex":[0.998835,0.00008667597,0.00029838,0.0002776645,0.0001798034,0.0003225111],"domain_scores_gemma":[0.9992206,0.0001318509,0.0002282333,0.0001910202,0.0001635693,0.00006473635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001635814,0.0002154688,0.9518817,0.0003133571,0.00008641074,0.00001446103,0.03816482,0.000001014659,0.002522214,0.002181993,0.0009749772,0.003479982],"study_design_scores_gemma":[0.000707084,0.00006704032,0.9713735,0.0001014135,0.00004321045,5.216427e-7,0.02482445,0.0000211062,0.0005090005,0.002126712,0.00008076373,0.0001452209],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911109,0.002576205,0.000008887516,0.000296368,0.00006696895,0.0003667445,0.000006626948,0.00001487936,0.005552459],"genre_scores_gemma":[0.9963322,0.0008997063,0.00009108344,0.000008408346,0.0001325553,0.00001446265,0.000002697712,0.000008597263,0.002510241],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01949176,"threshold_uncertainty_score":0.9931934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02283958177963598,"score_gpt":0.3068811552667149,"score_spread":0.284041573487079,"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."}}