{"id":"W1608830063","doi":"10.1007/978-3-540-74742-0_42","title":"Leveraging Many Simple Statistical Models to Adaptively Monitor Software Systems","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Fault detection and isolation; Simple (philosophy); System monitoring; Software; Component (thermodynamics); Fault (geology); Data mining; Real-time computing; Reliability engineering; Distributed computing; Artificial intelligence; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001900735,0.0007521311,0.000886363,0.001036481,0.0004332004,0.0007885562,0.003594065,0.0004713176,0.00001135302],"category_scores_gemma":[0.000131289,0.0006568456,0.0001420802,0.0007979093,0.0004534433,0.0009164464,0.001706811,0.0009723908,0.0001443703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008552798,"about_ca_system_score_gemma":0.0006534439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002450946,"about_ca_topic_score_gemma":0.00003100134,"domain_scores_codex":[0.9936523,0.00005821061,0.0009662538,0.002239236,0.001853146,0.001230882],"domain_scores_gemma":[0.9957511,0.001012846,0.0002893258,0.001879884,0.0005643824,0.0005023896],"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":[0.00001964866,0.00004073096,0.0002647367,0.0002181548,0.00002269262,0.0002165196,0.002005373,0.444605,0.00001267813,0.01781345,0.0001380573,0.5346429],"study_design_scores_gemma":[0.0002614858,0.0002633703,0.0003815684,0.0007369977,0.00001019226,0.0001174397,0.000001612144,0.9271715,0.0001220533,0.06820221,0.001629738,0.001101813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002776417,0.0004279083,0.9934305,0.0001200772,0.003599256,0.0009413873,0.0000272291,0.0004465147,0.0007294969],"genre_scores_gemma":[0.3530397,0.0000170154,0.6448232,0.0008690323,0.000883177,0.0000313539,0.000008829318,0.00006295423,0.0002647895],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5335411,"threshold_uncertainty_score":0.9995883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0425324232669908,"score_gpt":0.2744952122831364,"score_spread":0.2319627890161456,"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."}}