{"id":"W2074881976","doi":"10.1145/2806887","title":"The RAMCloud Storage System","year":2015,"lang":"en","type":"article","venue":"ACM Transactions on Computer Systems","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":270,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Samsung; Defense Advanced Research Projects Agency; NetApp; National Science Foundation; VMware; Cisco Systems; Semiconductor Research Corporation","keywords":"Computer science; Backup; Polling; Latency (audio); Operating system; Dram; Computer network; Computer data storage; RAID; Storage area network; Auxiliary memory; Server; File server; Converged storage; Data loss; Information repository; Computer hardware","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006221936,0.0002619254,0.0002712655,0.0001546261,0.000552458,0.0006083895,0.003964731,0.0001244723,3.828855e-7],"category_scores_gemma":[0.00003373562,0.0001860783,0.00009301765,0.0006265228,0.0001089848,0.0006757994,0.0001287798,0.0003576258,0.0003167256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003671808,"about_ca_system_score_gemma":0.00009315894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005874124,"about_ca_topic_score_gemma":0.00001253075,"domain_scores_codex":[0.9978217,0.0002022335,0.0004110311,0.0005636074,0.000560811,0.0004406127],"domain_scores_gemma":[0.9955403,0.0004369747,0.0001583623,0.003514751,0.0001814446,0.0001681332],"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":[0.00005027921,0.0002302151,0.00001676804,0.0001394321,0.0002589378,0.0003015637,0.001439195,0.2331366,0.00005521445,0.2558255,0.03590385,0.4726424],"study_design_scores_gemma":[0.001223617,0.0006349955,0.00004312439,0.0002177773,0.00002398148,0.0007411485,0.001415809,0.7140198,0.0004264818,0.001607825,0.2788675,0.000777931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003792779,0.0005048951,0.9839557,0.0009781022,0.01097472,0.0004296129,0.00001386835,0.002487347,0.0002764704],"genre_scores_gemma":[0.8641123,0.00002093419,0.1346343,0.0001009038,0.0004076988,0.0001862548,0.000002813725,0.00003315565,0.0005016654],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.863733,"threshold_uncertainty_score":0.7588053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03451363106089021,"score_gpt":0.2502271501895691,"score_spread":0.2157135191286789,"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."}}