{"id":"W2246314474","doi":"","title":"A PROBABILISTIC APPROACH TO DEFINING FREEWAY CAPACITY AND BREAKDOWN","year":2000,"lang":"en","type":"article","venue":"","topic":"Traffic control and management","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bottleneck; Probabilistic logic; Transport engineering; Probabilistic analysis of algorithms; Statistical model; Process (computing); Highway Capacity Manual; Traffic volume; Computer science; Engineering; Level of service; Machine learning; Artificial intelligence; Operations management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005504321,0.00008228063,0.00008989213,0.00002782862,0.00002502291,0.00002842228,0.0000514693,0.00002117813,0.0001526048],"category_scores_gemma":[0.000004809041,0.0000711077,0.00001523922,0.00006897398,0.00001039287,0.00003559631,0.00001209321,0.00004474535,0.00008136244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001588965,"about_ca_system_score_gemma":0.000001745336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006495356,"about_ca_topic_score_gemma":0.00007092772,"domain_scores_codex":[0.9995725,0.000004622429,0.00008280847,0.0001262293,0.00005752889,0.0001562909],"domain_scores_gemma":[0.9997934,0.00001222455,0.000002380734,0.0001136649,0.000004635971,0.00007367392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000107008,0.00006865519,0.00006039894,0.0001643173,0.00005905974,0.000001987312,0.001102195,0.4026732,0.0001403892,0.03218917,0.007856799,0.5556731],"study_design_scores_gemma":[0.00196214,0.0001389287,0.05690198,0.00005372756,0.0001013215,0.00003893717,0.0002513452,0.6292508,0.00005415654,0.001680451,0.3084607,0.00110546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3999687,0.00009946715,0.007655031,0.00009130069,0.00004582706,0.0003062022,0.000004372892,0.0006270822,0.591202],"genre_scores_gemma":[0.9924577,0.000006959295,0.006147699,0.0000993526,0.00001874642,0.00004557886,0.000001527363,0.00001004236,0.001212379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.592489,"threshold_uncertainty_score":0.2899688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00795766266874918,"score_gpt":0.1604653888532503,"score_spread":0.1525077261845011,"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."}}