{"id":"W3175048231","doi":"10.32866/001c.25224","title":"A Comprehensive Transit Accessibility and Equity Dashboard","year":2021,"lang":"en","type":"article","venue":"Findings","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Dashboard; Equity (law); Public transport; Business; Transit (satellite); Transport engineering; Baseline (sea); Computer science; Engineering; Data science; Political science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000359619,0.0001044787,0.000203236,0.00002597699,0.0005132247,0.0001758665,0.0002044783,0.0001123151,0.0008875068],"category_scores_gemma":[0.00008529878,0.0001048989,0.00007702877,0.0003147137,0.000376725,0.0004062114,0.00007423452,0.0001622667,0.00001569985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005680596,"about_ca_system_score_gemma":0.000199229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000672116,"about_ca_topic_score_gemma":0.001935593,"domain_scores_codex":[0.9986752,0.00009743126,0.0001934876,0.0004063025,0.0003055829,0.0003219591],"domain_scores_gemma":[0.9993588,0.0001033496,0.00003662861,0.0001935643,0.00014391,0.0001637811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003850398,0.0001416606,0.9617537,0.00013225,0.00003026472,0.00008550696,0.01813597,4.721586e-7,0.002911777,0.004279463,0.000811548,0.01167889],"study_design_scores_gemma":[0.0003353872,0.00001154209,0.9547631,0.00002238477,0.00002664341,9.948341e-7,0.001897273,0.000006523115,0.00195916,0.006772083,0.0340227,0.0001821594],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769657,0.000378887,0.0001373116,0.001364105,0.0001905801,0.0001355453,0.00002158617,0.00009411513,0.02071222],"genre_scores_gemma":[0.9981192,0.00004116536,0.0003148648,0.0003518956,0.0001000033,0.000005233976,0.00001386238,0.000006363299,0.001047362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03321116,"threshold_uncertainty_score":0.9717577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05960213511412883,"score_gpt":0.3654051286617658,"score_spread":0.305802993547637,"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."}}