{"id":"W1567863984","doi":"10.1002/atr.1314","title":"Modeling distributions of travel time variability for bus operations","year":2015,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Department of Transport and Main Roads, Queensland Government; China Scholarship Council","keywords":"Computer science; Reliability (semiconductor); Robustness (evolution); Normality; Travel time; Flexibility (engineering); Statistics; Econometrics; Transport engineering; Power (physics); Engineering; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001844665,0.0005126692,0.0004199996,0.001136016,0.0002267023,0.0009609913,0.0007826306,0.0005751685,0.0009817311],"category_scores_gemma":[0.007741634,0.0003216646,0.0007826068,0.001129685,0.0003625221,0.0007930743,0.0005687656,0.0008193284,0.000207893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223902,"about_ca_system_score_gemma":0.0005649845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02700161,"about_ca_topic_score_gemma":0.01266164,"domain_scores_codex":[0.9993525,0.0002532313,0.00002697514,0.000157717,0.0001263579,0.00008326665],"domain_scores_gemma":[0.997584,0.001482302,0.0003894536,0.0002234858,0.0002670752,0.00005359619],"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":[0.0000757622,0.00003380703,0.02232396,0.00002349839,0.00004479072,0.00007321224,0.00014388,0.9611425,0.0007798666,0.005728105,0.0004430912,0.009187575],"study_design_scores_gemma":[0.000002142756,0.00001916758,0.008745905,0.000004654526,0.000005870191,0.00002030121,0.00003518254,0.9892157,0.0001287131,0.001636134,0.0001782941,0.000007816996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8431667,0.0001577541,0.1533662,0.0002095157,0.00001203406,0.00007087956,0.001046702,0.0002163378,0.001753923],"genre_scores_gemma":[0.9929932,0.00008377196,0.005436604,0.000007396202,0.000006512191,0.00004082649,0.0007041281,0.00002295566,0.0007046117],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02700161,"threshold_uncertainty_score":0.05368888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02711827262556423,"score_gpt":0.3122607934518445,"score_spread":0.2851425208262803,"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."}}