{"id":"W611646440","doi":"","title":"Exploring transit ridership drivers in Toronto and Melbourne","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":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Transport engineering; Transit (satellite); Stock (firearms); Car ownership; Public transport; Business; Rail transit; Transit system; Geography; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.01379172,0.0004320641,0.0006097125,0.001054517,0.002020214,0.0003592886,0.000955725,0.000483586,0.001910962],"category_scores_gemma":[0.0006543924,0.0004747951,0.0002135824,0.002359944,0.002644309,0.004102158,0.00001167409,0.003233487,0.00004711841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004613618,"about_ca_system_score_gemma":0.001017018,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3125627,"about_ca_topic_score_gemma":0.912136,"domain_scores_codex":[0.9886475,0.001467511,0.00126727,0.00144324,0.004650913,0.002523561],"domain_scores_gemma":[0.9942243,0.001492225,0.0001538025,0.0005830284,0.002265825,0.001280785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009138304,0.0004678691,0.8165727,0.000364321,0.00005798107,0.0001980311,0.1332608,0.00005857805,0.003855276,0.03191515,0.0004832068,0.01185226],"study_design_scores_gemma":[0.001499222,0.0002187358,0.8762168,0.0001502725,0.00002285984,7.551424e-8,0.09519067,0.00002600459,0.0008355309,0.0020711,0.02327546,0.0004932475],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823125,0.0002786122,0.00009003325,0.00371414,0.0003971227,0.001841999,0.0001588267,0.0002497255,0.01095705],"genre_scores_gemma":[0.9949762,0.001750378,0.001012852,0.00004624136,0.0003854965,0.0005395882,0.0001432115,0.00008030343,0.00106579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5995733,"threshold_uncertainty_score":0.9997704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1621782986676654,"score_gpt":0.423947215971653,"score_spread":0.2617689173039875,"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."}}