{"id":"W3012444015","doi":"10.23919/fusion43075.2019.9011374","title":"Quickest Detection of Abnormal Vehicle Movements on Highways","year":2019,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Process (computing); Track (disk drive); Position (finance); State (computer science); Real-time computing; Vehicle dynamics; Artificial intelligence; Simulation; Engineering; Automotive engineering; Algorithm","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":[0.00005297158,0.00006988086,0.00009300649,0.00005824159,0.00001844964,0.000002042882,0.00008107751,0.0001009111,0.0001198123],"category_scores_gemma":[0.000002116318,0.00006638108,0.00002693826,0.00007900878,0.00001613477,0.00006150539,0.00001552941,0.0001146186,0.0004562719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003295324,"about_ca_system_score_gemma":0.000003518984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001668431,"about_ca_topic_score_gemma":0.00001267673,"domain_scores_codex":[0.9995936,0.000004390511,0.0001280034,0.00008207698,0.00006343968,0.0001285344],"domain_scores_gemma":[0.9997646,0.00001458413,0.00001707947,0.0001758654,0.00001016416,0.00001767726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007186568,0.0001177638,0.02607125,0.0001094668,0.0001083291,0.00000344755,0.0001691652,0.02654416,0.8733118,0.01244396,0.0002445114,0.06080425],"study_design_scores_gemma":[0.0004512499,0.0001879877,0.06341681,0.000009707923,0.000003321227,0.000001184227,0.00004908769,0.05856061,0.8755986,0.0001982945,0.00139674,0.0001264207],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683918,0.00001479181,0.001209159,0.00001482965,0.0002000354,0.00008855871,0.000002431193,0.0006312616,0.02944716],"genre_scores_gemma":[0.9994721,0.000007452569,0.00007137595,0.00003698931,0.00001092665,0.000003959029,0.000001560528,0.00001156073,0.0003840277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06067783,"threshold_uncertainty_score":0.5864604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004426025891742372,"score_gpt":0.1772570044118264,"score_spread":0.172830978520084,"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."}}