{"id":"W1069838147","doi":"","title":"Pedestrian Access to Transit: Identifying Redundancies and Gaps Using a Variable Service Area Analysis","year":2010,"lang":"en","type":"article","venue":"Transportation Research Board 89th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transport engineering; Headway; Service (business); Metropolitan area; Transit (satellite); Public transport; Level of service; Pedestrian; Catchment area; Population; Geography; Engineering; Business; Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001190432,0.0003058355,0.0004359095,0.003903729,0.0004675252,0.0007436944,0.0006429468,0.0003924157,0.001523068],"category_scores_gemma":[0.005320125,0.0002246561,0.0006762816,0.003280813,0.0002753405,0.0006659803,0.001063341,0.0003096036,0.0001940279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007527041,"about_ca_system_score_gemma":0.001035491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03601608,"about_ca_topic_score_gemma":0.03242649,"domain_scores_codex":[0.999139,0.0002722333,0.00006059221,0.0002067081,0.0002096546,0.0001118653],"domain_scores_gemma":[0.9975982,0.001072977,0.0004478917,0.0002615346,0.0004338732,0.0001856078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002245139,0.0001520461,0.9498827,0.00004007969,0.00008948622,0.0001490509,0.0006034232,0.01579793,0.0008453269,0.0008087078,0.0004711389,0.0309356],"study_design_scores_gemma":[0.000018202,0.0005039418,0.6613924,0.00002360924,0.00007920964,0.0002525521,0.002328264,0.3322909,0.0006211597,0.001371787,0.001088849,0.0000291276],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883008,0.00003243944,0.01043448,0.00003310263,0.000002604299,0.00003565637,0.0005748867,0.00008404076,0.0005020292],"genre_scores_gemma":[0.9923077,0.00001846067,0.006900521,0.000005105981,0.000003052889,0.00002372615,0.0005568939,0.000007548209,0.0001769246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03601608,"threshold_uncertainty_score":0.07161289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1453846560555973,"score_gpt":0.4552566772434079,"score_spread":0.3098720211878106,"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."}}