{"id":"W4319069025","doi":"10.1016/j.ymssp.2023.110159","title":"Universal source-free domain adaptation method for cross-domain fault diagnosis of machines","year":2023,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":140,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"China Scholarship Council","keywords":"Computer science; Discriminative model; Artificial intelligence; Fault (geology); Pattern recognition (psychology); Domain (mathematical analysis); Outlier; Classifier (UML); Data mining; Machine learning; Mathematics","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":[0.0006214257,0.0005869167,0.0006142271,0.0005035213,0.0003198174,0.0004102263,0.0006780702,0.0006407474,0.002774231],"category_scores_gemma":[0.001479154,0.000231182,0.0005388511,0.0004312205,0.0003445198,0.0007047612,0.0009750284,0.001085819,0.0008276149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002334303,"about_ca_system_score_gemma":0.0004907945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001502922,"about_ca_topic_score_gemma":0.001759875,"domain_scores_codex":[0.9997235,0.000067901,0.00001833511,0.00006839244,0.00009582692,0.00002605373],"domain_scores_gemma":[0.9995477,0.0001660802,0.00003083873,0.00008490786,0.0001547375,0.00001563816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002619845,0.00008799183,0.0006018595,0.0002389916,0.00009592748,0.000121029,0.0001285688,0.1276695,0.04642386,0.01270851,0.003446694,0.8082151],"study_design_scores_gemma":[0.000009906598,0.00004658989,0.000406794,0.000012478,0.00001691119,0.0001089767,0.00001101512,0.9849836,0.009744453,0.002403102,0.002244257,0.00001191875],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002657641,0.0001433198,0.9963832,0.00002256166,0.00002702318,0.0000101955,0.00001180952,0.0003322449,0.0004120019],"genre_scores_gemma":[0.3832009,0.0004319491,0.6102743,0.0001422421,0.00007519233,0.0001097077,0.0002595067,0.0002231778,0.005283088],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002774231,"threshold_uncertainty_score":0.009280741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920444434976939,"score_gpt":0.3021980572280576,"score_spread":0.2829936128782882,"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."}}