{"id":"W2946553955","doi":"10.1016/j.procs.2019.04.117","title":"Spatio-temporal Anomaly Detection in Intelligent Transportation Systems","year":2019,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Anomaly detection; Data mining; Anomaly (physics); Intelligent transportation system; Scheme (mathematics); Temporal database; Data stream mining; Real-time computing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005087315,0.000135211,0.0001446737,0.0004031016,0.0001286333,0.0002958412,0.0009819211,0.00005411184,0.000004672843],"category_scores_gemma":[0.000005921143,0.0001331256,0.00004071663,0.002016599,0.00007786134,0.001213552,0.00007698689,0.0001388009,0.0000985138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001373886,"about_ca_system_score_gemma":0.0001511275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001832135,"about_ca_topic_score_gemma":0.00008506305,"domain_scores_codex":[0.9982626,0.00001895258,0.0003495573,0.0006645156,0.000399199,0.0003051464],"domain_scores_gemma":[0.9990989,0.00002684353,0.0001402038,0.0004569839,0.0001785592,0.00009852208],"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":[0.00003515538,0.0005188578,0.1630756,0.0002832688,0.00001405289,0.00002250838,0.005528952,0.02292155,0.01855823,0.1674669,0.0001488099,0.6214261],"study_design_scores_gemma":[0.0001437898,0.0001728014,0.0436598,0.00003244499,0.000001414215,0.00002195534,0.00002223959,0.9284233,0.02462385,0.0009322748,0.001725992,0.0002400672],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.313403,0.00002211927,0.6852187,0.0000812657,0.0004802949,0.0004182325,6.885076e-7,0.0002368413,0.0001388963],"genre_scores_gemma":[0.9584652,0.000007490069,0.0412435,0.00007096662,0.0000598213,0.0001005513,0.000002198847,0.000006329428,0.00004391668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9055018,"threshold_uncertainty_score":0.5428703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009553193899687666,"score_gpt":0.2295163210543148,"score_spread":0.2199631271546271,"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."}}