{"id":"W4379383051","doi":"10.32920/23296241","title":"Anomaly Detection in Cloud Components","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cloud computing; Anomaly detection; Computer science; Robustness (evolution); Key (lock); Real-time computing; Autoencoder; Quality of service; Distributed computing; Data mining; Computer security; Computer network; Artificial intelligence; Operating system; Deep 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":[0.0006091236,0.0004975001,0.0005251975,0.001290762,0.0003353035,0.0007507757,0.0007530295,0.00062901,0.0004778468],"category_scores_gemma":[0.003163927,0.0003142432,0.000563177,0.001016935,0.0006134702,0.0009444162,0.0006492668,0.0006963829,0.0001641437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001120207,"about_ca_system_score_gemma":0.0005719592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007383076,"about_ca_topic_score_gemma":0.005161222,"domain_scores_codex":[0.9993649,0.00008805613,0.00003372083,0.0001868864,0.0002305781,0.00009592153],"domain_scores_gemma":[0.9987822,0.0004719118,0.0002433429,0.0001671495,0.0002876332,0.00004765538],"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":[0.0003272951,0.0001150568,0.03281612,0.00009847303,0.0001140408,0.0006118684,0.0002659816,0.7041439,0.03743711,0.008782563,0.001068621,0.2142191],"study_design_scores_gemma":[0.000001533297,0.0000132235,0.002165664,0.000001831961,0.00000489792,0.0000440498,0.00001172389,0.9933994,0.002877683,0.001315571,0.0001604517,0.000003991142],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4362455,0.0003122935,0.560816,0.0002319524,0.0000461797,0.00003709688,0.0001373566,0.001284292,0.0008893068],"genre_scores_gemma":[0.9668588,0.0000709077,0.03231343,0.00002250908,0.00001472495,0.00001030281,0.0001121754,0.00004438175,0.0005527255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007383076,"threshold_uncertainty_score":0.01468021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04768614865766477,"score_gpt":0.2821189447216154,"score_spread":0.2344327960639506,"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."}}