{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005895863,0.0006272304,0.0004624868,0.0006719208,0.0002057526,0.000391365,0.0007622064,0.0005532939,0.000459413],"category_scores_gemma":[0.001523155,0.0002702152,0.0004269569,0.000519941,0.0003032829,0.000649282,0.0004094627,0.0009752041,0.0001757451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008052069,"about_ca_system_score_gemma":0.0005725152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0100066,"about_ca_topic_score_gemma":0.008821747,"domain_scores_codex":[0.9996901,0.00004047888,0.00001855905,0.00009645239,0.0001079379,0.00004645124],"domain_scores_gemma":[0.9994324,0.0002419751,0.00006801783,0.00006070789,0.0001811902,0.00001560987],"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":[0.0001619652,0.0001238023,0.00444138,0.00005590427,0.0001085132,0.0001309278,0.00006432401,0.554152,0.02233925,0.002578628,0.001739059,0.4141043],"study_design_scores_gemma":[8.921608e-7,0.000009618865,0.0004566774,0.000001822784,0.000004143541,0.00001477017,0.00000184136,0.9965739,0.002390599,0.0003577071,0.0001851592,0.000002886193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07184545,0.0006206851,0.924145,0.000156616,0.00007048958,0.00002604421,0.0001095759,0.001933247,0.001092994],"genre_scores_gemma":[0.869315,0.0002889374,0.1277819,0.00007046467,0.00003593592,0.00003084104,0.0002772059,0.00005074049,0.002148973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0100066,"threshold_uncertainty_score":0.01989675,"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."}}