{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009491171,0.0006815555,0.0006604859,0.002620546,0.0003842435,0.0008756588,0.001120537,0.0009871023,0.0002834547],"category_scores_gemma":[0.006049796,0.0002232077,0.000340236,0.001501865,0.0004660826,0.00127517,0.0006413822,0.0007191762,0.0002646031],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003924866,"about_ca_system_score_gemma":0.0005300478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001744181,"about_ca_topic_score_gemma":0.002150741,"domain_scores_codex":[0.9985824,0.0002715072,0.00009746708,0.000403444,0.0005442118,0.0001009334],"domain_scores_gemma":[0.9939918,0.002472344,0.001481396,0.0006810135,0.001167749,0.0002056476],"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":[0.0005478512,0.0007142622,0.2071884,0.0002939372,0.0002218303,0.0006181235,0.0008374274,0.07003612,0.1393536,0.002682723,0.003711434,0.5737943],"study_design_scores_gemma":[0.00002515231,0.0004451323,0.09381187,0.00004175289,0.0001003592,0.001423617,0.0003442819,0.8218266,0.06882126,0.009157102,0.003913619,0.00008922918],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3597369,0.0003771423,0.6333743,0.0002422385,0.00005550645,0.0001273744,0.0004565363,0.004458501,0.001171536],"genre_scores_gemma":[0.8749179,0.0001879256,0.1234015,0.0000467342,0.00005940043,0.00007040413,0.0006573934,0.00008274585,0.0005758921],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002620546,"threshold_uncertainty_score":0.005019486,"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."}}