{"id":"W3124043893","doi":"10.1177/2399808320987093","title":"A data-driven complex network approach for planning sustainable and inclusive urban mobility hubs and services","year":2021,"lang":"en","type":"article","venue":"Environment and Planning B Urban Analytics and City Science","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Public transport; Equity (law); Multimodal transport; Business; Population; Sustainability; Transport engineering; Investment (military); Household income; Environmental economics; Geography; Economics; Marketing; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002344277,0.001546043,0.001441033,0.002359364,0.001100326,0.003537224,0.002788628,0.001827585,0.006367614],"category_scores_gemma":[0.007043263,0.001357849,0.001918566,0.00363281,0.001118502,0.002854883,0.002970435,0.001991224,0.0006563381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004476715,"about_ca_system_score_gemma":0.004510731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04575995,"about_ca_topic_score_gemma":0.07027372,"domain_scores_codex":[0.9987223,0.0005397156,0.00007166014,0.000321118,0.0002143559,0.0001309399],"domain_scores_gemma":[0.9965714,0.00225434,0.0002783791,0.0001459932,0.0005202161,0.0002296305],"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":[0.00001420243,0.00002332004,0.0007592744,0.00006014543,0.00003480512,0.00005536679,0.00004312434,0.9761638,0.0000776227,0.01455039,0.001008821,0.007209087],"study_design_scores_gemma":[0.000005541294,0.00000929386,0.0001028391,0.00001587796,0.000008464021,0.000008137371,0.0000738401,0.9837901,0.00003821422,0.01435363,0.001587612,0.000006366012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.013215,0.0003684682,0.9734226,0.001267394,0.00008634546,0.0002998458,0.002310968,0.0003644011,0.008664858],"genre_scores_gemma":[0.3151765,0.0009267249,0.6715479,0.0002929803,0.000105108,0.001450443,0.004495764,0.0002168426,0.005787625],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04575995,"threshold_uncertainty_score":0.09098721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04901984432395392,"score_gpt":0.3036725477176054,"score_spread":0.2546527033936515,"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."}}