{"id":"W4392845778","doi":"10.1145/3625007.3630112","title":"ROBUREC: Building a Robust Recommender using Autoencoders with Anomaly Detection","year":2023,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Recommender system; Anomaly detection; Computer science; Anomaly (physics); Artificial intelligence; 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":[0.001519206,0.0009866017,0.00150241,0.0006625468,0.0004968482,0.0008335356,0.002340378,0.00198039,0.001289938],"category_scores_gemma":[0.004516541,0.0008850899,0.001146024,0.0006044288,0.0005820855,0.001269662,0.000998585,0.002191594,0.001310819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006583859,"about_ca_system_score_gemma":0.001221505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02236702,"about_ca_topic_score_gemma":0.02955309,"domain_scores_codex":[0.9990937,0.0001749895,0.00005156771,0.000299007,0.0002873283,0.00009353179],"domain_scores_gemma":[0.997898,0.0009220412,0.0001474034,0.0003613926,0.0005922922,0.00007887278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002430445,0.0002464884,0.004101784,0.0001421049,0.0004927473,0.0002376437,0.0001392486,0.6256765,0.01907974,0.00496801,0.006141382,0.3385313],"study_design_scores_gemma":[0.000006973078,0.00003252887,0.0001621239,0.000003519168,0.00001197648,0.00002890117,0.000003633712,0.9978255,0.001005481,0.0004967129,0.0004152694,0.000007441465],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01432861,0.0004272579,0.9819962,0.0001836212,0.00007259633,0.00005298128,0.0001173576,0.002128341,0.0006929698],"genre_scores_gemma":[0.3663368,0.0004117781,0.6257733,0.0004992944,0.0001478654,0.0002105571,0.0008162225,0.0002308251,0.005573234],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02236702,"threshold_uncertainty_score":0.04447371,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.044557122635001,"score_gpt":0.2691403065238563,"score_spread":0.2245831838888553,"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."}}