{"id":"W4404687722","doi":"10.1063/5.0245089","title":"Implemented transit signal priorities based on range of traffic volume","year":2024,"lang":"en","type":"article","venue":"AIP conference proceedings","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Range (aeronautics); Transit (satellite); Volume (thermodynamics); Computer science; SIGNAL (programming language); Traffic volume; Transport engineering; Environmental science; Engineering; Public transport; Aerospace engineering; Physics","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":[0.0009288751,0.0005390399,0.0004318031,0.000861283,0.0005502137,0.001256067,0.0009232752,0.0002803165,0.002194141],"category_scores_gemma":[0.00317387,0.0002662165,0.0001639355,0.0005099241,0.0002184636,0.0007949114,0.0004084023,0.0008095152,0.0003814586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000819631,"about_ca_system_score_gemma":0.001349743,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003987222,"about_ca_topic_score_gemma":0.006831014,"domain_scores_codex":[0.9994406,0.0001034134,0.0000342074,0.0001485943,0.0001640498,0.0001090845],"domain_scores_gemma":[0.9982433,0.0004909076,0.000103548,0.0002306307,0.0007925517,0.0001390125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003064344,0.001356011,0.03042957,0.0002272351,0.0001721701,0.0002326181,0.0006603116,0.2361516,0.160751,0.02381308,0.005922925,0.5372191],"study_design_scores_gemma":[0.00005731255,0.0003232034,0.00377315,0.00001158055,0.00005711221,0.00007540551,0.00007733356,0.9347,0.0551217,0.003720197,0.002045949,0.00003702198],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3458709,0.000209841,0.6382693,0.0002063949,0.000372023,0.0002449174,0.0003024004,0.004917982,0.009606287],"genre_scores_gemma":[0.9251705,0.00003213106,0.07292993,0.00003520678,0.00002879935,0.0000386317,0.0001056492,0.00007559191,0.001583477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003987222,"threshold_uncertainty_score":0.007928014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01405298985854123,"score_gpt":0.2244032137309844,"score_spread":0.2103502238724432,"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."}}