{"id":"W627592587","doi":"","title":"Measuring, Describing and Modeling Travel Time Reliability","year":2010,"lang":"en","type":"article","venue":"Transportation Research Board 89th Annual MeetingTransportation Research Board","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reliability (semiconductor); Computer science; Cluster analysis; Travel time; Process (computing); Duration (music); Transport engineering; Task (project management); Kilometer; Operations research; Engineering","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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.006919529,0.0004250633,0.0004560498,0.001352346,0.0008131097,0.0002549864,0.0005848462,0.0004175157,0.000197363],"category_scores_gemma":[0.0003216286,0.0004616798,0.000156023,0.00136517,0.0006367182,0.001043174,0.00001862188,0.00302742,0.0001120443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000128422,"about_ca_system_score_gemma":0.0001560439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002012515,"about_ca_topic_score_gemma":0.004765367,"domain_scores_codex":[0.9933246,0.000382749,0.001033225,0.0009703106,0.002786814,0.001502317],"domain_scores_gemma":[0.9963135,0.0004332651,0.00006142619,0.0006460053,0.00180768,0.0007381652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002480252,0.00173064,0.07130097,0.006186713,0.0008707938,0.0006126204,0.05116775,0.1491413,0.4566151,0.05996643,0.08054353,0.1193839],"study_design_scores_gemma":[0.004345403,0.0008863198,0.2662717,0.0008378007,0.0001503564,0.000004173191,0.01127253,0.6609295,0.02226635,0.00560729,0.02496681,0.002461822],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9620039,0.0001379323,0.02638192,0.0005900107,0.0002745482,0.001665472,0.0001993337,0.00327725,0.005469668],"genre_scores_gemma":[0.991782,0.0004926571,0.006465233,0.00002977663,0.0001746016,0.0004189641,0.0001888131,0.0001321178,0.0003157998],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5117882,"threshold_uncertainty_score":0.9997835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07546869405523231,"score_gpt":0.3173288499970836,"score_spread":0.2418601559418512,"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."}}