{"id":"W2004954545","doi":"10.1109/dsn.2014.51","title":"Ocasta: Clustering Configuration Settings for Error Recovery","year":2014,"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":"University of Toronto","funders":"","keywords":"Cluster analysis; Configuration Management (ITSM); Configuration design; Error detection and correction","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":[0.0005749651,0.00007725799,0.0001093262,0.00003579665,0.0001324508,0.0001009483,0.0002608834,0.00005129876,0.000009715468],"category_scores_gemma":[0.0001078397,0.00005970415,0.00005587017,0.00008854851,0.00001289785,0.0005146289,0.00006002386,0.00003861239,0.0000577502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000264137,"about_ca_system_score_gemma":0.00002517634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001303762,"about_ca_topic_score_gemma":0.00000997841,"domain_scores_codex":[0.9992518,0.00002667265,0.0001962258,0.0002469833,0.0001047466,0.0001735481],"domain_scores_gemma":[0.9993144,0.0001512707,0.00006416417,0.0003413804,0.00008879623,0.00004001793],"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":[0.00008591846,0.0001163365,0.003912067,0.0010171,0.00005283029,0.000001165587,0.002204619,0.004142446,0.004195964,0.05804118,0.04298657,0.8832438],"study_design_scores_gemma":[0.0005605836,0.0002960793,0.002040438,0.00005022352,0.000004368551,0.00001245821,0.00004956827,0.9219324,0.005576897,0.00320988,0.06600998,0.0002571404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01691834,0.000006577438,0.9772159,0.001123885,0.0007756896,0.0002447649,6.518969e-7,0.0002429861,0.003471238],"genre_scores_gemma":[0.9173748,0.000001267232,0.08050547,0.0008869066,0.0001627038,0.00004343739,0.000003267525,0.000005960439,0.001016222],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9177899,"threshold_uncertainty_score":0.2434665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459315565618415,"score_gpt":0.2496226915313144,"score_spread":0.2350295358751303,"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."}}