{"id":"W2962903771","doi":"10.1109/tits.2018.2820044","title":"Cooperative Vehicle Speed Fault Diagnosis and Correction","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Network Time Synchronization Technologies","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Automotive industry; Fault (geology); CAN bus; Engineering; Traction control system; Computer science; Vehicle dynamics; Telecommunications network; Control engineering; Function (biology); Traction (geology); Real-time computing; Automotive engineering; Computer network","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":[0.0004047598,0.000515403,0.0005917811,0.0005979522,0.0004983014,0.0005413695,0.001045195,0.0008059503,0.0006814207],"category_scores_gemma":[0.001605877,0.0001561731,0.0003162683,0.0003598696,0.0004543568,0.0006413819,0.0008458751,0.0005584595,0.0002440789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005735048,"about_ca_system_score_gemma":0.0008354146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00336188,"about_ca_topic_score_gemma":0.002023077,"domain_scores_codex":[0.9995408,0.00005617073,0.00001888178,0.0001471155,0.0001715274,0.000065479],"domain_scores_gemma":[0.9992698,0.0002054522,0.0001344197,0.0001421643,0.0002173211,0.000030897],"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":[0.0003417195,0.0001591345,0.003184455,0.00009874008,0.00004331161,0.0003867836,0.0002896188,0.5182309,0.04185594,0.01094475,0.001695389,0.4227693],"study_design_scores_gemma":[0.00002171056,0.0001244686,0.0004794994,0.000004594821,0.00001569713,0.0001484784,0.00002678785,0.9830124,0.01249314,0.002358055,0.001305458,0.000009659946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04876244,0.000130596,0.948165,0.0001168857,0.00006249332,0.00005218695,0.00001699771,0.0008570739,0.001836348],"genre_scores_gemma":[0.9330248,0.00006409986,0.06514811,0.00003302553,0.00002293326,0.00004300187,0.00003099595,0.00001796041,0.001615162],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00336188,"threshold_uncertainty_score":0.006684601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0222610441362146,"score_gpt":0.2547184075678029,"score_spread":0.2324573634315883,"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."}}