{"id":"W2465615181","doi":"10.1115/1.4033907","title":"Design and Evaluation of Model-Based Health Monitoring Scheme for Automated Manual Transmission","year":2016,"lang":"en","type":"article","venue":"Journal of Dynamic Systems Measurement and Control","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hefei University of Technology; Hefei University; National Natural Science Foundation of China; Canada Excellence Research Chairs, Government of Canada; U.S. Department of Energy","keywords":"Fault detection and isolation; Scheme (mathematics); Reliability engineering; Manual transmission; Fault (geology); Transmission (telecommunications); Set (abstract data type); Computer science; Identification (biology); Control engineering; Data mining; Engineering; Real-time computing; Artificial intelligence; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004291121,0.0001260263,0.0003898224,0.0001418332,0.00004950065,0.00002331473,0.00005107726,0.0000635588,4.998785e-7],"category_scores_gemma":[0.00003114447,0.00008482859,0.00006422827,0.00004102898,0.00001172951,0.000108534,0.000001191659,0.00004875396,1.227978e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002790403,"about_ca_system_score_gemma":0.0001290657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004033948,"about_ca_topic_score_gemma":0.0000010179,"domain_scores_codex":[0.9982478,0.0002019468,0.0006526602,0.00008977766,0.0006569804,0.0001508138],"domain_scores_gemma":[0.9989181,0.00007035292,0.0003014286,0.00007141982,0.0005348745,0.0001038297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004463863,0.00003351603,0.0003673807,0.0007337622,0.0003315443,4.39372e-7,0.0001590668,0.3131239,0.5814655,0.00000700666,0.00005368213,0.1032779],"study_design_scores_gemma":[0.008258016,0.0002717703,0.0004448737,0.001221271,0.0001020219,0.00001165442,0.00006143388,0.9885353,0.0009593654,0.00001471406,0.00003177698,0.00008777159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.108807,0.008786228,0.880937,0.0001212652,0.000446312,0.0008379809,0.000004021096,0.00005537344,0.000004774724],"genre_scores_gemma":[0.998876,0.00006543131,0.0009235238,0.000003737339,0.00006009795,0.00004831832,1.673206e-7,0.00001715612,0.000005513712],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.890069,"threshold_uncertainty_score":0.345921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0441024262170155,"score_gpt":0.2904614750777566,"score_spread":0.2463590488607411,"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."}}