{"id":"W3032697887","doi":"10.1007/978-3-030-47358-7_39","title":"Exploring Deep Anomaly Detection Methods Based on Capsule Net","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brock University; Queen's University; University of Ottawa","funders":"","keywords":"Computer science; Artificial intelligence; Autoencoder; Pattern recognition (psychology); Benchmark (surveying); Classifier (UML); Anomaly detection; Deep learning; ENCODE; Anomaly (physics); Cartography","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":[0.0008148394,0.0008226493,0.0007819389,0.0009220879,0.0003244059,0.001196007,0.001726256,0.0008121541,0.001983054],"category_scores_gemma":[0.002157923,0.0004565248,0.0005875897,0.0007512469,0.0005460742,0.002083674,0.001399078,0.001504035,0.0004983876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005750898,"about_ca_system_score_gemma":0.0006070064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002874625,"about_ca_topic_score_gemma":0.003544649,"domain_scores_codex":[0.9997128,0.00005876413,0.00001221272,0.00007257169,0.000102088,0.00004155706],"domain_scores_gemma":[0.9990466,0.0005470612,0.00008099642,0.000105231,0.0001613747,0.00005869328],"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":[0.0004256852,0.0002210766,0.003386567,0.0001512969,0.0001740147,0.0001505891,0.00008786793,0.3559849,0.01752766,0.04567424,0.00466591,0.5715501],"study_design_scores_gemma":[0.000002959883,0.00001912594,0.0001077621,0.000003447333,0.00000705752,0.00001621196,0.00000462468,0.9917365,0.001058763,0.006670679,0.0003700467,0.000002771694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02104573,0.0004011154,0.9759514,0.0001669868,0.00005352149,0.00002121204,0.00004713154,0.0009840692,0.001328839],"genre_scores_gemma":[0.5153552,0.000784705,0.4750747,0.0002454342,0.0001499098,0.00007321488,0.0004637095,0.0003735341,0.007479593],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002874625,"threshold_uncertainty_score":0.006633937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06106865309463925,"score_gpt":0.2897956188595806,"score_spread":0.2287269657649414,"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."}}