{"id":"W4362514754","doi":"10.1109/tnnls.2023.3262277","title":"Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks and Learning Systems","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Basic and Applied Basic Research Foundation of Guangdong Province; National Natural Science Foundation of China","keywords":"Computer science; Spatial analysis; Representation (politics); Fault detection and isolation; Graph; Data mining; Temporal database; Aliasing; Artificial intelligence; Theoretical computer science; 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":[0.0008695815,0.00113269,0.0009803636,0.001444493,0.0004257879,0.0009229489,0.001376291,0.0009329817,0.001091085],"category_scores_gemma":[0.002839515,0.0004257718,0.0009576182,0.001037376,0.000668443,0.001885808,0.00174533,0.001336891,0.0002883523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000949265,"about_ca_system_score_gemma":0.001607544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008216452,"about_ca_topic_score_gemma":0.005982765,"domain_scores_codex":[0.9993926,0.0001097754,0.00004291477,0.0001854768,0.0001706821,0.00009850127],"domain_scores_gemma":[0.9991523,0.0002994672,0.000182196,0.0001025697,0.0002074705,0.00005589149],"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":[0.0001976933,0.0001410234,0.002930303,0.00009907842,0.00006616102,0.0001974657,0.0001528314,0.7568492,0.009071412,0.01105652,0.001221994,0.2180162],"study_design_scores_gemma":[0.00000401734,0.00001792605,0.000221374,0.000002435955,0.000008143534,0.00001661624,0.000006661496,0.9961129,0.001044989,0.002371752,0.0001885914,0.000004586652],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0164585,0.0001227227,0.9823056,0.00007856233,0.000008194529,0.00002092925,0.0000539303,0.0006528951,0.0002986559],"genre_scores_gemma":[0.7045006,0.0003017631,0.2920348,0.0001350476,0.00006682657,0.0001577218,0.0007144665,0.0001684059,0.001920469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008216452,"threshold_uncertainty_score":0.01633722,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02571993995410982,"score_gpt":0.2537131477583465,"score_spread":0.2279932078042367,"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."}}