{"id":"W2317818493","doi":"10.3141/2537-05","title":"Who, What, When, and Where","year":2015,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transit (satellite); Public transport; TRIPS architecture; Service (business); Business; Transport engineering; Population; Level of service; Demographic economics; Marketing; Economics; Engineering; Environmental health; Medicine","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":[0.001567001,0.0002378488,0.0004573698,0.001192089,0.002933069,0.006209546,0.0007424976,0.001274077,0.01833628],"category_scores_gemma":[0.003987113,0.0002966266,0.0002899711,0.00182901,0.003193602,0.003996581,0.001302027,0.001205599,0.00629625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008673616,"about_ca_system_score_gemma":0.02061497,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5569336,"about_ca_topic_score_gemma":0.6511253,"domain_scores_codex":[0.99839,0.0002761608,0.00007771063,0.0002683341,0.0004319026,0.0005559375],"domain_scores_gemma":[0.9970822,0.0002681324,0.0003326023,0.00009944724,0.00117891,0.001038776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00008322841,0.00009384102,0.1648979,0.001000914,0.00006659218,0.00100986,0.02736828,0.0003000213,0.001700975,0.01976546,0.4325632,0.3511497],"study_design_scores_gemma":[0.00001129508,0.00003287835,0.1093851,0.001302597,0.00007144214,0.0004578923,0.07458699,0.0004592642,0.0006915123,0.007471516,0.805455,0.00007450597],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1796681,0.03480645,0.008062055,0.4352439,0.00456381,0.0004201679,0.01056611,0.0006704486,0.3259988],"genre_scores_gemma":[0.8027551,0.03258258,0.005675045,0.01544736,0.001107617,0.0001186236,0.003343981,0.0001626209,0.1388071],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5569336,"threshold_uncertainty_score":0.8913515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1620179428476127,"score_gpt":0.43362172224363,"score_spread":0.2716037793960173,"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."}}