{"id":"W4254189127","doi":"10.32920/ryerson.14644503","title":"BRT omnibus : how bus rapid transit enhances mobility","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban Transport Systems Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Bus rapid transit; Popularity; Flexibility (engineering); Transit (satellite); Mode (computer interface); Transport engineering; Computer science; Public transport; Business; Engineering; Economics; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002875561,0.0005439444,0.001045098,0.0001568364,0.0000437249,0.0002022368,0.0004420062,0.0005320006,0.002137937],"category_scores_gemma":[0.000009345433,0.0005447228,0.0007175039,0.0002954986,0.00003684582,0.0001302568,0.00005087911,0.0007338045,0.00003423864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001566589,"about_ca_system_score_gemma":0.00008045467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009314137,"about_ca_topic_score_gemma":0.003382197,"domain_scores_codex":[0.9977861,0.00005616151,0.0005501611,0.0007691424,0.0004213874,0.0004170188],"domain_scores_gemma":[0.9983571,0.00004090874,0.00006900052,0.001233431,0.000136051,0.00016353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006483435,0.001112735,0.01400914,0.03672709,0.02293867,0.001304211,0.01552661,0.6488929,0.1825345,0.0001906007,0.02072105,0.05597766],"study_design_scores_gemma":[0.002677866,0.0002087329,0.07265739,0.003112898,0.006623391,0.00008192174,0.006510661,0.2533108,0.5630907,0.0004363215,0.07834823,0.01294103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7802063,0.01136266,0.1908394,0.0003095701,0.002381384,0.0007083707,0.0001395451,0.001753733,0.01229907],"genre_scores_gemma":[0.9956628,0.0006203392,0.001607907,0.00001850225,0.0002429312,0.000124528,0.0002656917,0.00008263193,0.001374652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3955821,"threshold_uncertainty_score":0.9997004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186146257470153,"score_gpt":0.1882645006783246,"score_spread":0.176403038103623,"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."}}