{"id":"W2035670852","doi":"10.1080/03081060008717659","title":"Estimation of time‐dependent, stochastic route travel times using artificial neural networks","year":2000,"lang":"en","type":"article","venue":"Transportation Planning and Technology","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Artificial neural network; Travel time; Estimation; Computer science; Transport engineering; Engineering; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004711876,0.00045623,0.0003014492,0.0006775273,0.0002013132,0.0003989791,0.0004937194,0.0004913941,0.0004235085],"category_scores_gemma":[0.003815107,0.0003014826,0.0003277521,0.0006365682,0.0001791699,0.0006452242,0.0002131882,0.0004542676,0.0001124918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006198106,"about_ca_system_score_gemma":0.0005542414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01587241,"about_ca_topic_score_gemma":0.01630746,"domain_scores_codex":[0.9997216,0.00007399586,0.00002065069,0.00005642057,0.0001046372,0.00002267585],"domain_scores_gemma":[0.9989564,0.0005531791,0.000207107,0.00006026962,0.0002016916,0.0000212962],"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":[0.00002629977,0.00002162799,0.002275128,0.00001384245,0.00002297515,0.00001864042,0.00001447574,0.9727054,0.0006374513,0.0005757058,0.0001355366,0.0235529],"study_design_scores_gemma":[0.000001278816,0.000005598988,0.0006098785,0.000001330136,0.000002174638,0.000004855257,0.000002712102,0.9987863,0.0002359593,0.0002821466,0.0000648441,0.000003060867],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2146996,0.0001358858,0.7830467,0.0001108127,0.00003386692,0.00002303224,0.0001908915,0.0005033463,0.00125593],"genre_scores_gemma":[0.9215705,0.0001246191,0.0769157,0.00001897769,0.00002346304,0.00004570204,0.0003263618,0.00002474858,0.0009498748],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01587241,"threshold_uncertainty_score":0.03156006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008304728214769465,"score_gpt":0.2190699148662046,"score_spread":0.2107651866514351,"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."}}