{"id":"W3010579604","doi":"10.1109/globecom38437.2019.9013491","title":"Assessing the Integrity of Traffic Data through Short Term State Prediction","year":2019,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; Queen's University","funders":"","keywords":"Anomaly detection; Computer science; Global Positioning System; Offset (computer science); Detector; Autoregressive integrated moving average; Real-time computing; Time series; Term (time); Calibration; Data mining; Mathematics; Statistics; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001223997,0.0007782265,0.0007493382,0.002033127,0.0005115441,0.001311733,0.0009378158,0.0007132758,0.0005071397],"category_scores_gemma":[0.006565696,0.0002739812,0.0003143855,0.001228028,0.000439463,0.002909682,0.0006855426,0.001141508,0.0004160992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000466421,"about_ca_system_score_gemma":0.0007741016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00362002,"about_ca_topic_score_gemma":0.003995789,"domain_scores_codex":[0.9989723,0.0001170738,0.0001090576,0.0002628861,0.0004348637,0.0001038176],"domain_scores_gemma":[0.9942961,0.001881878,0.001232545,0.0008716137,0.001549964,0.0001677931],"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":[0.0004950912,0.0006102272,0.1565825,0.0001586841,0.0001805017,0.0003021057,0.0002780114,0.3283122,0.02951919,0.003367606,0.001866718,0.4783272],"study_design_scores_gemma":[0.00000296578,0.0001072732,0.0131451,0.00001422791,0.00002311785,0.0001001768,0.00005189555,0.9770384,0.007347163,0.001393407,0.0007547328,0.00002141537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4616771,0.0005873792,0.5323787,0.0003611984,0.0001641046,0.00006852717,0.000800081,0.002263375,0.001699492],"genre_scores_gemma":[0.9716415,0.0001641806,0.02673716,0.00002597519,0.00004573311,0.00002259994,0.0008762462,0.0000322951,0.000454115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00362002,"threshold_uncertainty_score":0.007197917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04637239495633012,"score_gpt":0.3025154891343342,"score_spread":0.2561430941780041,"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."}}