{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01339058,0.0005296935,0.0008908644,0.003168742,0.004272708,0.001599801,0.001708986,0.0006086176,0.001592011],"category_scores_gemma":[0.001197988,0.0005759796,0.0003258817,0.0148305,0.001546063,0.003154578,0.00003427467,0.002733191,0.00003908117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002297341,"about_ca_system_score_gemma":0.002282889,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2150405,"about_ca_topic_score_gemma":0.6776217,"domain_scores_codex":[0.9870991,0.001384844,0.001504656,0.001854628,0.005527788,0.002628972],"domain_scores_gemma":[0.9886217,0.001351216,0.0002590384,0.0008637269,0.006556169,0.002348161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001177263,0.0004302531,0.8964229,0.0008152426,0.000474185,0.0001334074,0.07295781,0.002241598,0.01818111,0.004985337,0.001028123,0.001152744],"study_design_scores_gemma":[0.001319375,0.0001703828,0.9387069,0.0002409197,0.0004803623,2.321656e-7,0.02771764,0.0005108573,0.001418214,0.00316614,0.02538676,0.0008822606],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9828606,0.0001470419,0.004998954,0.005785681,0.000331794,0.002518442,0.000644916,0.0003145184,0.002398071],"genre_scores_gemma":[0.990667,0.0001794822,0.00684802,0.0002956142,0.0003679507,0.0003204276,0.0003903029,0.00009001496,0.000841212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4625812,"threshold_uncertainty_score":0.9996692,"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."}}