{"id":"W4220839771","doi":"10.1145/3523057","title":"Machine Learning for Computer Systems and Networking: A Survey","year":2022,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Global Water Futures; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Deutsche Forschungsgemeinschaft; Canada First Research Excellence Fund; Joint Programming Initiative Water challenges for a changing world; Pennsylvania State University","keywords":"Computer science; Machine learning; Artificial intelligence; Overhead (engineering); De facto; Domain (mathematical analysis); Set (abstract data type); Taxonomy (biology); Human–computer interaction; Operating system; Programming language","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01397821,0.0006007475,0.00178047,0.0003110229,0.001124566,0.0007671064,0.002096069,0.0002897559,0.000009182057],"category_scores_gemma":[0.0003914536,0.000575422,0.0003435175,0.001147131,0.00004925346,0.000170493,0.003433825,0.001186472,0.00001033181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001353409,"about_ca_system_score_gemma":0.0001399761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005927274,"about_ca_topic_score_gemma":0.00005628707,"domain_scores_codex":[0.9884056,0.008311322,0.0009719637,0.001223629,0.0004038022,0.0006836927],"domain_scores_gemma":[0.9884262,0.009358185,0.0008723995,0.001079294,0.0001092948,0.0001546033],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001712056,0.00002211415,0.0001056404,0.001982602,0.00009742953,0.000006608174,0.00006321029,0.001023599,4.012586e-9,0.0002073373,0.0008111384,0.9956786],"study_design_scores_gemma":[0.0001306312,0.0001528018,0.00005289464,0.0009818221,0.00003602164,0.00009203626,7.827715e-7,0.3547777,6.747567e-9,0.00002886764,0.6433513,0.0003951482],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000002751261,0.6164009,0.377056,0.000006118777,0.005557806,0.0006504678,0.00001429919,0.0002851537,0.00002652536],"genre_scores_gemma":[0.0001172336,0.9916588,0.005589619,0.00003952667,0.001903201,0.00006062373,0.000434956,0.00008217103,0.0001138819],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9952835,"threshold_uncertainty_score":0.9996697,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1022091545996425,"score_gpt":0.315509840785039,"score_spread":0.2133006861853965,"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."}}