{"id":"W2147247575","doi":"10.1109/icpc.2011.23","title":"Anomaly Detection by Monitoring Filesystem Activities","year":2011,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Notice; Computer science; Anomaly detection; Baseline (sea); Context (archaeology); Process (computing); Anomaly (physics); Point (geometry); Software; State (computer science); System call; File system; Software bug; Real-time computing; Data mining; Operating system; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001784328,0.00008494113,0.0000972934,0.00004208022,0.0001076123,0.00005002276,0.0003192838,0.00005700823,0.00002103052],"category_scores_gemma":[0.000007284098,0.00006525576,0.00004155817,0.0001494932,0.00001704242,0.0007362824,0.0000751182,0.00006152262,0.00007529585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004427491,"about_ca_system_score_gemma":0.00001286457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000291265,"about_ca_topic_score_gemma":0.000005917937,"domain_scores_codex":[0.999295,0.00003342696,0.000144471,0.0002183101,0.0001394253,0.0001693592],"domain_scores_gemma":[0.9994746,0.00002847197,0.00004760512,0.0003728346,0.00002956434,0.00004689753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003256847,0.0002688102,0.5538637,0.0003247221,0.00008603571,0.00001158068,0.009739054,0.000007485321,0.0357463,0.001449197,0.002066638,0.3964039],"study_design_scores_gemma":[0.0002274675,0.000186934,0.06470922,0.00004118011,0.000004538609,0.00003400766,0.0005408109,0.003477905,0.9284256,0.0001891974,0.001832803,0.0003303558],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6536034,0.00006598607,0.3374709,0.000008554765,0.001150838,0.00009482999,5.685755e-7,0.0004709275,0.007133946],"genre_scores_gemma":[0.9950527,0.000004103212,0.00425605,0.000009688956,0.00006893411,0.00002441073,1.375308e-7,0.000004269771,0.0005797112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8926793,"threshold_uncertainty_score":0.2661053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808081646640393,"score_gpt":0.2030975643208252,"score_spread":0.1850167478544213,"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."}}