{"id":"W6998689723","doi":"","title":"An Anomaly Detection System for Smart Manufacturing Using Deep Learning","year":2021,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Research Council Canada","keywords":"Anomaly detection; Autoencoder; Deep learning; Residual; Convolutional neural network; Thresholding; Focus (optics); Anomaly (physics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004744423,0.0006343382,0.0005900057,0.0007238869,0.0003388137,0.0004899139,0.00124355,0.0007724146,0.001975048],"category_scores_gemma":[0.0009087251,0.0003000434,0.0004735497,0.0004301553,0.0002943753,0.000933307,0.001116139,0.001008864,0.0006610331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008702244,"about_ca_system_score_gemma":0.0007609559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003430949,"about_ca_topic_score_gemma":0.004850641,"domain_scores_codex":[0.999685,0.00002053971,0.00001725067,0.0001214823,0.0001157222,0.00003998531],"domain_scores_gemma":[0.9996606,0.00006328477,0.00005183984,0.00005577128,0.0001378014,0.00003078887],"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":[0.000547113,0.0003550316,0.005863446,0.0001106464,0.0001260073,0.0004162668,0.0001336099,0.1237098,0.1324393,0.004427372,0.006909998,0.7249615],"study_design_scores_gemma":[0.000007721969,0.00006331728,0.0007917722,0.000003417782,0.00001117787,0.00006706818,0.000007097487,0.9779801,0.01837102,0.00136339,0.001322606,0.00001122232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04498282,0.0001303281,0.9405882,0.0001795984,0.00008346383,0.00005284258,0.0002047368,0.01275898,0.001018976],"genre_scores_gemma":[0.6603686,0.0001059197,0.3342898,0.0002294972,0.00004482036,0.0001033358,0.0006503413,0.0002002241,0.004007431],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003430949,"threshold_uncertainty_score":0.00682199,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06768313866499705,"score_gpt":0.303259693765128,"score_spread":0.2355765551001309,"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."}}