{"id":"W4367626136","doi":"10.3390/app13095545","title":"A New Macroscopic Traffic Flow Characterization Incorporating Traffic Emissions","year":2023,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Traffic control and management","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"University of Hail","keywords":"Traffic congestion reconstruction with Kerner's three-phase theory; Traffic flow (computer networking); Traffic congestion; Traffic bottleneck; Greenhouse gas; Traffic generation model; Environmental science; Presumption; Traffic optimization; Computer science; Transport engineering; Floating car data; Engineering; Real-time computing; Computer network","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":[0.0003067404,0.0008625499,0.0006039588,0.001051448,0.0003783372,0.001141082,0.0007647699,0.0005853379,0.0006903803],"category_scores_gemma":[0.0007072391,0.0002085859,0.0006357479,0.0009805219,0.0004111998,0.001987963,0.0006006955,0.0005652048,0.0001458634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007401165,"about_ca_system_score_gemma":0.0009206855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007094651,"about_ca_topic_score_gemma":0.004307134,"domain_scores_codex":[0.9996464,0.00006568413,0.00001655006,0.0001095392,0.0001141881,0.00004756924],"domain_scores_gemma":[0.9997986,0.00003604664,0.00003364225,0.00003956767,0.00007760475,0.00001463575],"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":[0.0000323382,0.00008649061,0.005210449,0.00005060411,0.00002684341,0.00009305621,0.00006563777,0.9303422,0.01755694,0.01710311,0.00071906,0.02871323],"study_design_scores_gemma":[0.00000148477,0.00001947204,0.0007743664,0.000001958215,0.000005265919,0.00002322199,0.00001050665,0.9964046,0.0010805,0.001047025,0.0006200668,0.00001159881],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1107508,0.0001386918,0.8811187,0.00009922008,0.00008182375,0.00008840206,0.0003481416,0.0005778596,0.006796424],"genre_scores_gemma":[0.952747,0.0002087606,0.04404589,0.00003075054,0.00003464978,0.0001019912,0.0005296546,0.0000527773,0.00224858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007094651,"threshold_uncertainty_score":0.01410669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01311851448749692,"score_gpt":0.2208180810696284,"score_spread":0.2076995665821315,"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."}}