{"id":"W3163723672","doi":"10.1016/j.ins.2021.05.021","title":"A three-way clustering approach for novelty detection","year":2021,"lang":"en","type":"article","venue":"Information Sciences","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cluster analysis; Novelty detection; Computer science; Novelty; Set (abstract data type); Artificial intelligence; Data mining; Core (optical fiber); Reduction (mathematics); Key (lock); Machine learning; Pattern recognition (psychology); Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003838287,0.00006258558,0.00006367359,0.0001067137,0.0004967264,0.0004572576,0.0003858198,0.00003940262,0.000005204711],"category_scores_gemma":[0.00004326703,0.00005627997,0.00004955291,0.0008118302,0.00005288591,0.002291136,0.0001136006,0.00004616625,0.00001599468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002778377,"about_ca_system_score_gemma":0.00006598355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002123226,"about_ca_topic_score_gemma":0.00002667884,"domain_scores_codex":[0.9992654,0.000006707504,0.0002199742,0.0001611255,0.0002008677,0.0001459111],"domain_scores_gemma":[0.9994249,0.00003438568,0.0001118339,0.0002105923,0.0001808683,0.00003742753],"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":[0.000002573626,0.0000302364,0.00006265855,0.00003030692,0.000005072456,9.612785e-8,0.0005004477,0.00225859,0.002865457,0.06534313,0.0004267074,0.9284747],"study_design_scores_gemma":[0.00009816472,0.00004233729,0.000557326,0.000003019538,0.000001449285,0.00002649406,0.00014008,0.9476386,0.02936006,0.003351337,0.01867963,0.0001014578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007695651,0.00001027767,0.9900396,0.0003293541,0.000112065,0.0002041575,0.000002994997,0.0002411511,0.008290867],"genre_scores_gemma":[0.5187711,0.000003168421,0.4806433,0.0003544457,0.00002920025,0.0001617435,0.000003840801,0.000001346709,0.00003179855],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.94538,"threshold_uncertainty_score":0.4409345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03917483380950819,"score_gpt":0.2780907780157492,"score_spread":0.238915944206241,"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."}}