{"id":"W4388115974","doi":"10.36001/phmconf.2023.v15i1.3520","title":"Automotive Electronic Control Unit Ground Line Health Monitoring Method","year":2023,"lang":"en","type":"article","venue":"Annual Conference of the PHM Society","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Motors (Canada)","funders":"","keywords":"Automotive engineering; Automotive industry; CAN bus; Electronic control unit; Engineering; Fault (geology); Reliability (semiconductor); Controller (irrigation); Embedded system; Computer science; Real-time computing; Reliability engineering; Electrical engineering","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":[0.0002882223,0.0006785017,0.0004053873,0.001276715,0.0002790265,0.0006897055,0.0009143592,0.0004774104,0.006330841],"category_scores_gemma":[0.001176661,0.0001772995,0.0001603502,0.0007615417,0.000176079,0.00056603,0.000432722,0.0004256644,0.002294343],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004806118,"about_ca_system_score_gemma":0.0004700908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001820476,"about_ca_topic_score_gemma":0.001461165,"domain_scores_codex":[0.9991705,0.00005576505,0.00004673416,0.000285457,0.0003846117,0.0000569492],"domain_scores_gemma":[0.9993774,0.00007330968,0.0001052988,0.00008110124,0.0003434722,0.00001936358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00060115,0.0002776525,0.02558543,0.0004013063,0.00007052666,0.0002957074,0.0002141444,0.01021643,0.08882448,0.003534852,0.01213075,0.8578476],"study_design_scores_gemma":[0.0001815505,0.001372454,0.08098517,0.000153709,0.0001549292,0.001682093,0.0003731037,0.5080329,0.326475,0.003455646,0.076944,0.0001895613],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.14431,0.001209858,0.8014598,0.0002370945,0.0005482831,0.001074536,0.002688811,0.01247597,0.03599555],"genre_scores_gemma":[0.8047913,0.0004533056,0.1709805,0.0002726163,0.0001332906,0.0007584907,0.002206036,0.0001770894,0.02022747],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006330841,"threshold_uncertainty_score":0.02117878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03094948058450474,"score_gpt":0.3036137827301791,"score_spread":0.2726643021456744,"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."}}