{"id":"W2339274406","doi":"10.15760/trec.87","title":"Assessing Transit Fare Equity in Utah Using a Geographic Information System","year":2014,"lang":"en","type":"report","venue":"","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Equity (law); Transit (satellite); Public transport; Population; Social planner; Geography; Business; Transport engineering; Geographic information system; Social equality; Economics; Engineering; Political science; Cartography; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001981336,0.0003105445,0.0002846541,0.003304311,0.001006203,0.001610665,0.0007010368,0.0004332483,0.0008917561],"category_scores_gemma":[0.007763959,0.0001610131,0.0003025058,0.005237515,0.0004773201,0.001137913,0.001696729,0.0002698767,0.0001071802],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004676839,"about_ca_system_score_gemma":0.002592556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.294792,"about_ca_topic_score_gemma":0.3648321,"domain_scores_codex":[0.998664,0.0003845698,0.00009514007,0.0001881768,0.0005635148,0.000104631],"domain_scores_gemma":[0.9969915,0.001035617,0.0005956576,0.0002481737,0.0009832105,0.0001457076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00014574,0.0002179266,0.9014631,0.00007361505,0.0001186192,0.0001855995,0.001213849,0.04463736,0.001027255,0.002299769,0.00150064,0.04711658],"study_design_scores_gemma":[0.00002924796,0.0002308341,0.8587247,0.00003500616,0.00008161803,0.00005902507,0.002489167,0.1312575,0.001017518,0.001512661,0.004523839,0.00003886253],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911979,0.00005338825,0.003136376,0.0001038559,0.00000391731,0.0001041597,0.001637777,0.0001035898,0.003659056],"genre_scores_gemma":[0.990352,0.00004375823,0.007196702,0.00001483162,0.000004966462,0.00007430433,0.001735268,0.000006300112,0.0005718866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.294792,"threshold_uncertainty_score":0.5861522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1143061047483809,"score_gpt":0.4052893913951566,"score_spread":0.2909832866467758,"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."}}