{"id":"W4378650033","doi":"10.32920/23257217","title":"Towards Inclusion: The Budd Car Train from Sudbury to White River","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Science North; University of Toronto","funders":"","keywords":"Inclusion (mineral); Institution; Vulnerability (computing); White (mutation); Poverty; Service (business); Isolation (microbiology); Sociology; Geography; Gender studies; Political science; Business; Law; Computer security; Social science; Marketing; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004202747,0.0005092803,0.0005000546,0.0008623481,0.04677848,0.009515463,0.001679636,0.002986637,0.009183991],"category_scores_gemma":[0.005425562,0.0003947336,0.0003051074,0.001315261,0.0220137,0.006718103,0.008340486,0.005789381,0.0007415172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01227678,"about_ca_system_score_gemma":0.01051736,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.242104,"about_ca_topic_score_gemma":0.3636224,"domain_scores_codex":[0.9925621,0.005312041,0.00006893501,0.0003051934,0.0006790865,0.001072663],"domain_scores_gemma":[0.9963489,0.001683066,0.0002032693,0.000169249,0.0004014106,0.001194073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00003470936,0.00002557609,0.0006528434,0.00006354452,0.000002576048,0.001122885,0.967605,0.00003196258,0.0004007519,0.01256417,0.01226377,0.005232167],"study_design_scores_gemma":[0.000002071692,0.00001637403,0.0007661145,0.0001112305,0.000002426949,0.0001314894,0.9301997,0.00002260303,0.0001433037,0.0003556619,0.06823744,0.00001151565],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7253642,0.002405485,0.001676547,0.05507794,0.001467214,0.0001014982,0.0001247631,0.00005161872,0.2137307],"genre_scores_gemma":[0.9537477,0.0009545889,0.0004375132,0.003341866,0.00008790768,0.00006885649,0.00003090276,0.00005746781,0.0412732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7578961,"threshold_uncertainty_score":0.4813895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05280909814136106,"score_gpt":0.3305761525621455,"score_spread":0.2777670544207844,"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."}}