{"id":"W4247085377","doi":"10.32920/ryerson.14647785","title":"Smart Transit Dynamic Optimization and Informatics","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Dynamic pricing; Queue; Component (thermodynamics); Queueing theory; Operations research; Process (computing); Scheduling (production processes); Real-time computing; Mathematical optimization; Economics; Computer network; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007853777,0.0007894341,0.0009048579,0.0004841326,0.0004152808,0.00153181,0.0006480085,0.0008274138,0.004687863],"category_scores_gemma":[0.00221026,0.0004362319,0.0007085196,0.0007378553,0.001188859,0.001762102,0.001151076,0.001252478,0.0002509534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002193804,"about_ca_system_score_gemma":0.001309999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007771438,"about_ca_topic_score_gemma":0.004920285,"domain_scores_codex":[0.9995472,0.0001722601,0.00001501671,0.0001108998,0.00007594498,0.0000787383],"domain_scores_gemma":[0.9991376,0.0004953186,0.0001283931,0.00009284182,0.00008872235,0.00005702346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002750624,0.00002597289,0.0004454178,0.00003606893,0.00002325166,0.00002389123,0.00001894057,0.9436738,0.0002119288,0.04754185,0.00116251,0.006808945],"study_design_scores_gemma":[0.000006327622,0.00001592602,0.0002281583,0.000005571776,0.000004351437,0.00000860765,0.00002048867,0.9705936,0.0001047055,0.02782607,0.001181603,0.000004452811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1864634,0.001708554,0.7646155,0.004167468,0.0003414649,0.0001308262,0.0006721948,0.0006462317,0.04125423],"genre_scores_gemma":[0.9610204,0.00067698,0.02913638,0.00024136,0.0001002725,0.00007322025,0.000273314,0.00009430311,0.008383898],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007771438,"threshold_uncertainty_score":0.01591724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006371842414821381,"score_gpt":0.203016224653246,"score_spread":0.1966443822384246,"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."}}