{"id":"W2157535433","doi":"10.1145/1551609.1551643","title":"Exploring data reliability tradeoffs in replicated storage systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Reliability (semiconductor); Throughput; Computer data storage; Idle; Exploit; Data reliability; Storage area network; Architecture; Information repository; Embedded system; Computer network; Reliability engineering; Distributed computing; Operating system; Database; Engineering; Wireless; Computer security","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":[0.00343811,0.0004122214,0.000490082,0.0006965426,0.0006176514,0.00138245,0.001047755,0.0008247155,0.001167473],"category_scores_gemma":[0.01905384,0.0004291303,0.0002569067,0.000566611,0.0006649424,0.003214655,0.0009009341,0.0007514697,0.0001549908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001124313,"about_ca_system_score_gemma":0.0004958981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001565433,"about_ca_topic_score_gemma":0.001567601,"domain_scores_codex":[0.9982294,0.0008211535,0.00006175077,0.0001545616,0.0004880956,0.0002449529],"domain_scores_gemma":[0.9851151,0.01179405,0.0006798278,0.0008479536,0.001350055,0.0002130017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001108692,0.0002250767,0.01151092,0.0003585784,0.0001214103,0.0006216774,0.0009898836,0.8540247,0.03015823,0.05498537,0.00103844,0.04485694],"study_design_scores_gemma":[0.00004294184,0.0002358513,0.002612064,0.00001785447,0.00004557098,0.000208442,0.0003858382,0.9602584,0.00660978,0.02877556,0.0007756377,0.00003202377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8662666,0.002064659,0.1243653,0.0009347223,0.00003901457,0.00005363772,0.0001046089,0.0001673206,0.006004093],"genre_scores_gemma":[0.9943844,0.0001556572,0.005065687,0.00001171792,0.00001140484,0.0000153341,0.00001936188,0.0000193813,0.0003170561],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00343811,"threshold_uncertainty_score":0.01818269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2059717759587804,"score_gpt":0.3055685779062168,"score_spread":0.09959680194743639,"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."}}