{"id":"W2041938145","doi":"10.1109/noms.2012.6211882","title":"Interactive learning of alert signatures in High Performance Cluster system logs","year":2012,"lang":"en","type":"article","venue":"","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"National Institute for Materials Science; Natural Sciences and Engineering Research Council of Canada; Dalhousie University","keywords":"Computer science; Anomaly detection; Signature (topology); Visualization; Feature (linguistics); Data mining; Cluster (spacecraft); Simple (philosophy); Machine learning; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002293702,0.0007075776,0.0006417921,0.001588855,0.0003026838,0.0009806509,0.001245831,0.0008397539,0.001019825],"category_scores_gemma":[0.01362709,0.0002960612,0.000252671,0.0006197575,0.0003247874,0.001154619,0.0009379601,0.0009358012,0.0004784477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005650623,"about_ca_system_score_gemma":0.0008352745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003373081,"about_ca_topic_score_gemma":0.005077064,"domain_scores_codex":[0.9990444,0.0003065123,0.00005091822,0.000234032,0.0002901909,0.00007392317],"domain_scores_gemma":[0.9869322,0.009734865,0.0008912354,0.0009236769,0.001056199,0.0004619032],"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":[0.001657366,0.001695106,0.0755606,0.0002148496,0.000164491,0.0004628724,0.001169446,0.1734331,0.03321593,0.000866996,0.005322375,0.7062369],"study_design_scores_gemma":[0.00001855495,0.000108775,0.006022051,0.000004585144,0.000008611793,0.00004629961,0.00005555424,0.9848931,0.007703673,0.0007913142,0.0003347031,0.00001277529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6731813,0.0001287755,0.29805,0.0003677122,0.00003821161,0.0002071409,0.0004835118,0.02619217,0.00135119],"genre_scores_gemma":[0.9352554,0.00003037707,0.0633787,0.00005395046,0.00001533184,0.0000582802,0.0004674236,0.0001269631,0.0006134703],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003373081,"threshold_uncertainty_score":0.01213044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006903645971703883,"score_gpt":0.2260938502631949,"score_spread":0.219190204291491,"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."}}