{"id":"W2615498866","doi":"10.1155/2017/9184891","title":"Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Computer science; Shortest path problem; Reliability (semiconductor); Path (computing); Cluster analysis; Algorithm; Data mining; Mathematical optimization; Artificial intelligence; Mathematics; Graph; Theoretical computer science","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":[0.0004237262,0.0006936656,0.0008059531,0.0005423297,0.0005526016,0.0006838272,0.001249066,0.0007661205,0.001747906],"category_scores_gemma":[0.001012877,0.0004957166,0.0007768343,0.0007097999,0.000450333,0.001111667,0.0007813523,0.0008024234,0.0001611174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008723679,"about_ca_system_score_gemma":0.001925295,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02162684,"about_ca_topic_score_gemma":0.01046993,"domain_scores_codex":[0.9996709,0.00006912916,0.00001308965,0.0001022144,0.00006462415,0.00008010249],"domain_scores_gemma":[0.9996425,0.000143989,0.00004975661,0.00002267258,0.0001007619,0.00004020428],"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":[0.00001996515,0.000009017864,0.0002872316,0.00001438926,0.000008451045,0.00002579436,0.00001970399,0.9903731,0.0004064988,0.001796008,0.0001933417,0.006846542],"study_design_scores_gemma":[0.000002335512,0.000009827724,0.00005480028,8.934077e-7,0.00000215686,0.000006300237,0.000005912213,0.9989781,0.0001422596,0.0006802738,0.0001141426,0.000002940531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0540817,0.0001369029,0.9434284,0.0001235025,0.00002409465,0.00005027866,0.00009554498,0.0002647339,0.001794813],"genre_scores_gemma":[0.9018303,0.0001864913,0.09412467,0.00002851018,0.00001072112,0.000161586,0.0002700228,0.0000489351,0.003338723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02162684,"threshold_uncertainty_score":0.04300189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440911382399292,"score_gpt":0.3010009889531438,"score_spread":0.2865918751291509,"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."}}