{"id":"W4408715825","doi":"10.1109/itsc58415.2024.10920052","title":"Toward a Fair and Efficient Ramp Metering Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Smart Parking Systems Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"University of California","keywords":"Metering mode; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002211492,0.00008527012,0.00009606243,0.0001243294,0.00001881389,0.0001548984,0.00006992501,0.00003835414,0.00003067083],"category_scores_gemma":[0.00001028957,0.00007042674,0.00002689535,0.0001754671,0.00001284203,0.00003521866,0.00005125555,0.0001158079,0.00008646852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004581299,"about_ca_system_score_gemma":0.000006925013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001746593,"about_ca_topic_score_gemma":6.96275e-7,"domain_scores_codex":[0.9993632,0.0000132851,0.0001015737,0.0001621054,0.0001554772,0.0002043114],"domain_scores_gemma":[0.9997626,0.00004854137,0.0000018296,0.000118703,0.000007511494,0.00006082589],"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":[0.00002900071,0.0001276661,0.0015295,0.02269507,0.001416119,0.0005380662,0.02162125,0.4139935,0.2649492,0.02979042,0.0478884,0.1954218],"study_design_scores_gemma":[0.00005949238,0.000008792216,0.0001781753,0.00004926982,0.000003724885,0.00005415085,0.0001363536,0.9794106,0.00270635,0.00001042648,0.01727394,0.0001086523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6228871,0.004067933,0.2475146,0.00006471486,0.0007984576,0.0003549621,0.000003235715,0.002185331,0.1221237],"genre_scores_gemma":[0.9971352,0.00001289364,0.002054704,0.000003141643,0.00008519574,0.00003502355,0.000001107156,0.00002887297,0.000643919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5654172,"threshold_uncertainty_score":0.2871919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03332849915911744,"score_gpt":0.2505357033068842,"score_spread":0.2172072041477668,"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."}}