{"id":"W4386245887","doi":"10.1007/s12555-022-0241-2","title":"Just-in-time Learning-aided Nonlinear Fault Detection for Traction Systems of High-speed Trains","year":2023,"lang":"en","type":"article","venue":"International Journal of Control Automation and Systems","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Traction (geology); Train; Computer science; Fault detection and isolation; Salient; Nonlinear system; Control theory (sociology); Real-time computing; Artificial intelligence; 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":[0.0005761494,0.0006679832,0.0008783729,0.0002952407,0.0004883219,0.0007383793,0.0006048901,0.000846154,0.002297481],"category_scores_gemma":[0.00263146,0.0002351822,0.0003366714,0.0002542075,0.0004921657,0.0009680212,0.0008262092,0.0009862484,0.0003650685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004151353,"about_ca_system_score_gemma":0.001315627,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004694037,"about_ca_topic_score_gemma":0.007020828,"domain_scores_codex":[0.999608,0.00007525443,0.0000299555,0.00007706196,0.0001291971,0.00008062956],"domain_scores_gemma":[0.9989311,0.0005201714,0.0001042078,0.0000964439,0.0003055053,0.0000425071],"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":[0.001466732,0.0001980699,0.002922575,0.000373062,0.00009460241,0.0002320642,0.000268254,0.5025989,0.02348238,0.006248438,0.002108205,0.4600067],"study_design_scores_gemma":[0.00001334091,0.0001117209,0.0004969464,0.000006790893,0.000009211969,0.00004105377,0.00000946136,0.9950078,0.003115083,0.0008547647,0.0003267202,0.000007237608],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09245983,0.000428177,0.9038496,0.0002239739,0.0001634676,0.00006226912,0.00007145839,0.0008886531,0.001852618],"genre_scores_gemma":[0.9596934,0.00009674342,0.03811443,0.00005166719,0.00003763417,0.00003792102,0.00009327498,0.00002723885,0.001847603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004694037,"threshold_uncertainty_score":0.009333432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01071593712292899,"score_gpt":0.2507157714445317,"score_spread":0.2399998343216027,"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."}}