{"id":"W2805217410","doi":"10.7939/r3wm1473r","title":"Processing Improvement of Map-Matching for Travel Time Prediction Model","year":2017,"lang":"en","type":"article","venue":"University of Alberta Library","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Matching (statistics); Artificial intelligence; Data mining; Mathematics; Statistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006287852,0.0007273691,0.0005981501,0.001018748,0.0004876609,0.0009887216,0.001070757,0.0004375098,0.003374609],"category_scores_gemma":[0.002107651,0.0003509462,0.0009732206,0.001430257,0.000185543,0.001416891,0.000787991,0.0007000943,0.001394746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004978713,"about_ca_system_score_gemma":0.001201674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01817246,"about_ca_topic_score_gemma":0.006986374,"domain_scores_codex":[0.9993041,0.00008321444,0.00004865585,0.0002257066,0.0002717866,0.00006668668],"domain_scores_gemma":[0.9995373,0.00007294507,0.00003488759,0.00008840886,0.0002519591,0.00001435916],"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":[0.0002231753,0.0001366922,0.008176965,0.0001674716,0.000105044,0.0001870187,0.0001860662,0.4040174,0.01093184,0.00893082,0.007141117,0.5597964],"study_design_scores_gemma":[0.00000694241,0.00002704153,0.001405826,0.000005094699,0.0000204648,0.00003744476,0.00002872704,0.9895214,0.00454861,0.001842277,0.002545024,0.00001121199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02789064,0.0001480704,0.9669607,0.00009102597,0.00008178875,0.00006688135,0.0004047607,0.002111063,0.002245162],"genre_scores_gemma":[0.6673066,0.0006103029,0.321621,0.00007004218,0.00008408974,0.0002662047,0.00291392,0.0002257875,0.006902068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01817246,"threshold_uncertainty_score":0.03613335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006183910329061324,"score_gpt":0.1693949245708139,"score_spread":0.1632110142417526,"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."}}