{"id":"W3106791815","doi":"10.1109/dsaa49011.2020.00017","title":"Ensemble of Hierarchical Temporal Memory for Anomaly Detection","year":2020,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Research and Development; Science and Engineering Research Council","keywords":"Anomaly detection; Computer science; Univariate; Encoder; Anomaly (physics); Multivariate statistics; Artificial intelligence; Ensemble learning; Data mining; Pattern recognition (psychology); Machine learning","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":[0.002012012,0.0009695122,0.001255578,0.001553689,0.0006191567,0.0007518447,0.002054314,0.0009182207,0.001518611],"category_scores_gemma":[0.005995009,0.0003748101,0.0008698645,0.001499106,0.0004828488,0.002322281,0.001453823,0.001710421,0.0005870375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007301463,"about_ca_system_score_gemma":0.001325476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005658288,"about_ca_topic_score_gemma":0.008667517,"domain_scores_codex":[0.9992681,0.0001432588,0.00005298626,0.0002289045,0.0002017737,0.0001049177],"domain_scores_gemma":[0.9976804,0.0009036852,0.0002240336,0.0004854209,0.0005829502,0.0001233948],"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":[0.0002602711,0.0002375588,0.008075514,0.00009932038,0.0002801857,0.0001239211,0.0001219208,0.1979029,0.007248812,0.007078193,0.00499845,0.7735729],"study_design_scores_gemma":[0.000004992897,0.00005146226,0.0005256644,0.000007522875,0.00002590818,0.00005036289,0.0000122736,0.9917672,0.003085357,0.003972317,0.0004877977,0.000009172393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05210903,0.001031317,0.9430218,0.0001814808,0.0001229972,0.00004746371,0.0002285964,0.002298984,0.0009583705],"genre_scores_gemma":[0.7119755,0.0005234265,0.2828709,0.0002496842,0.0001584667,0.0001246542,0.001035635,0.0001531332,0.002908608],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005658288,"threshold_uncertainty_score":0.01125073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02437757581031336,"score_gpt":0.2524361550823725,"score_spread":0.2280585792720592,"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."}}