{"id":"W4322707015","doi":"10.1109/tim.2023.3250308","title":"Reliable and Intelligent Fault Diagnosis With Evidential VGG Neural Networks","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"China Scholarship Council; Royal Society","keywords":"Artificial neural network; Computer science; Artificial intelligence; Fault (geology); Noise (video); Machine learning; Reliability (semiconductor); Process (computing); Data mining; Image (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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001970471,0.0001789485,0.00013511,0.0001913776,0.0001455861,0.00008258111,0.00005082329,0.00005592923,0.00005027483],"category_scores_gemma":[0.000002332195,0.0001658069,0.00003130358,0.0002601116,0.00003623294,0.000186281,0.000001308954,0.0001693205,0.000007658577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001065829,"about_ca_system_score_gemma":0.000007262904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008551696,"about_ca_topic_score_gemma":0.0002597781,"domain_scores_codex":[0.9990044,0.00002165539,0.0002139652,0.0002119622,0.0003441033,0.0002038626],"domain_scores_gemma":[0.999669,0.00002722079,0.00002654053,0.0001230218,0.00005007161,0.0001041099],"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":[0.00009298897,0.000147728,0.00447745,0.0001819628,0.0002207622,0.000008657106,0.0006743034,0.4641282,0.001314665,0.0000419925,0.00341605,0.5252953],"study_design_scores_gemma":[0.001882992,0.0007557956,0.009488055,0.0004380484,0.000242059,0.000025053,0.0005814046,0.8089715,0.1729562,0.00006521132,0.003845236,0.0007484246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5690413,0.0002102057,0.4272957,0.0004280368,0.000771829,0.0008337064,0.00001445188,0.001180878,0.000223989],"genre_scores_gemma":[0.9960265,0.00278038,0.000435861,0.0001127149,0.0000265064,0.0005579878,0.000005828982,0.00003153317,0.00002275934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5245469,"threshold_uncertainty_score":0.6761407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02777630287197556,"score_gpt":0.2647597088848442,"score_spread":0.2369834060128687,"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."}}