{"id":"W1983537108","doi":"10.3141/2168-14","title":"Exclusive Truck Facilities in Toronto, Ontario, Canada","year":2010,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of Toronto","funders":"Infrastructure Canada","keywords":"Truck; Transport engineering; Traffic flow (computer networking); Travel time; Engineering; Computer science; Automotive engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002655142,0.0004482605,0.000286398,0.001020312,0.00317389,0.001390818,0.001213613,0.0004087238,0.01200738],"category_scores_gemma":[0.001031302,0.0003665191,0.0005019454,0.003604548,0.0005805765,0.000498333,0.0007472379,0.0004055508,0.0007040023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0520673,"about_ca_system_score_gemma":0.06778251,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9981977,"about_ca_topic_score_gemma":0.9994621,"domain_scores_codex":[0.9993945,0.0000387455,0.00001795972,0.00005856731,0.0002241294,0.0002660907],"domain_scores_gemma":[0.9989437,0.00007197976,0.0001155747,0.00004114595,0.0005150305,0.0003124491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008140849,0.0003325272,0.5097162,0.001614841,0.0002509566,0.003557076,0.006523557,0.07895092,0.003022909,0.04078346,0.1935632,0.1608703],"study_design_scores_gemma":[0.0001251986,0.0001694612,0.7940231,0.0004658235,0.0001307077,0.0005283976,0.01084796,0.04335118,0.0008050128,0.00308317,0.1463178,0.0001522234],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8214061,0.003888287,0.003986458,0.002652922,0.0001385219,0.0003684591,0.05546637,0.0003091728,0.1117837],"genre_scores_gemma":[0.9447272,0.001923757,0.002057079,0.0001450006,0.00001286247,0.00007526119,0.01013573,0.00003918693,0.04088389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0520673,"threshold_uncertainty_score":0.3777764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05206389883305234,"score_gpt":0.3704335640849076,"score_spread":0.3183696652518552,"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."}}