{"meta":{"query_hash":"a978b40d8155","filters":{"venue":"2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS)"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/a978b40d8155","api":"https://metacan.xera.ac/api/v1/cohort?venue=2022+IEEE+11th+Data+Driven+Control+and+Learning+Systems+Conference+%28DDCLS%29"},"results":[{"id":"W4293794915","doi":"10.1109/ddcls55054.2022.9858467","title":"A Segmental Autoencoder-based Fault Detection for Nonlinear Dynamic Systems: An Interpretable Learning Framework","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS)","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Autoencoder; Nonlinear system; Fault detection and isolation; Representation (politics); Computer science; Residual; Kernel (algebra); Artificial intelligence; Fault (geology); Generator (circuit theory); Pattern recognition (psychology); Algorithm; Deep learning; Mathematics; Power (physics)","score_opus":0.015543642356140806,"score_gpt":0.25147237479709206,"score_spread":0.23592873244095125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293794915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004524877,0.00012549914,0.99485767,0.0000489379,0.000008670563,0.000008023267,0.000017797187,0.00009704456,0.00031151992],"genre_scores_gemma":[0.56225544,0.0005262181,0.433494,0.00013204958,0.00008959359,0.00009449658,0.00022099112,0.00007243805,0.0031146766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998011,0.000052174,0.000012137477,0.00006458143,0.000050945368,0.000019147159],"domain_scores_gemma":[0.9997571,0.00011308868,0.000031258645,0.00003180493,0.00005693152,0.000009836766],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005639247,0.00062808115,0.0005736623,0.0003640127,0.00018656558,0.00041950215,0.00073631277,0.00073323946,0.0008079658],"category_scores_gemma":[0.0010265651,0.00024965967,0.00055100565,0.00028719724,0.00068049534,0.00079469517,0.00060432684,0.0010482075,0.00018757676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007507649,0.00006002357,0.00077817036,0.00013280007,0.00009343544,0.00014241389,0.00014793429,0.771945,0.023414152,0.036802467,0.0007829154,0.1656256],"study_design_scores_gemma":[0.0000013356051,0.000025453375,0.00011096394,0.0000046133227,0.0000066783123,0.000015528209,0.0000033490667,0.9950891,0.0013824055,0.0030374066,0.00031880918,0.0000044050116],"about_ca_topic_score_codex":0.0022637425,"about_ca_topic_score_gemma":0.0021516636,"teacher_disagreement_score":0.0022637425,"about_ca_system_score_codex":0.00039241492,"about_ca_system_score_gemma":0.0004910326,"threshold_uncertainty_score":0.0045011044},"labels":[],"label_agreement":null}]}