{"id":"W4352981169","doi":"10.1109/iscmi56532.2022.10068441","title":"Anomaly Detection with Convolutional Autoencoder for Predictive Maintenance","year":2022,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Anomaly detection; Autoencoder; Computer science; Downtime; Sliding window protocol; Anomaly (physics); Benchmark (surveying); Artificial intelligence; Data set; Data modeling; Pattern recognition (psychology); Data mining; Deep learning; Window (computing)","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":[0.0001296428,0.00006973252,0.00006307497,0.00006322395,0.0005535564,0.00003206351,0.0003058469,0.00001693824,0.00005728661],"category_scores_gemma":[0.00000434995,0.00006038348,0.0000414316,0.0003246134,0.00003456544,0.0001875334,0.0001196274,0.00008849186,0.000003806367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000121658,"about_ca_system_score_gemma":0.00006636803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002878696,"about_ca_topic_score_gemma":0.0000149498,"domain_scores_codex":[0.999275,0.00001798902,0.0001058759,0.0002912993,0.000157866,0.0001519369],"domain_scores_gemma":[0.9995351,0.00003529348,0.00006371456,0.0002294805,0.00009949088,0.00003696056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002121726,0.0003305415,0.0007130658,0.00001403408,0.0000754756,0.000003606568,0.000316071,0.01508042,0.005385342,0.9146262,0.0143995,0.04884356],"study_design_scores_gemma":[0.000373853,0.0009310259,0.003138934,0.000001603789,0.000005976697,0.00009491333,0.00009610932,0.869912,0.005554734,0.01207613,0.1076472,0.0001676118],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001249101,0.000008367373,0.9940685,0.000617235,0.00006630649,0.0004333217,0.00001789847,0.0005072057,0.003032037],"genre_scores_gemma":[0.8542209,8.818307e-7,0.1405249,0.0003524449,0.00002546066,0.001887866,0.000003344741,0.000006278367,0.002977968],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9025501,"threshold_uncertainty_score":0.4257564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007550529174472557,"score_gpt":0.2108238368150575,"score_spread":0.2032733076405849,"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."}}