{"id":"W2171837867","doi":"10.1109/isnetcod.2011.5978915","title":"Pipelined Regeneration with Regenerating Codes for Distributed Storage Systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced Data Storage Technologies","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Regeneration (biology); Computer science; Redundancy (engineering); Process (computing); Distributed data store; Data redundancy; Computer data storage; Computer network; Distributed computing; Database; Computer hardware; Operating system; Biology","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":[0.0004442307,0.0003753747,0.0003456931,0.0007535873,0.0005473992,0.0005027724,0.0008120346,0.0005651742,0.001544845],"category_scores_gemma":[0.001505905,0.0002252249,0.0003258233,0.0006945943,0.0007312483,0.001349908,0.0006993242,0.0006291269,0.000410019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007224232,"about_ca_system_score_gemma":0.0008338995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001592604,"about_ca_topic_score_gemma":0.001607302,"domain_scores_codex":[0.99958,0.00006254506,0.00003200371,0.00007187985,0.0001979891,0.00005550706],"domain_scores_gemma":[0.9990201,0.0002603274,0.0001383168,0.0002580321,0.0002747209,0.00004853405],"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":[0.0008670669,0.0002180343,0.001145963,0.000560143,0.00004278918,0.0004852583,0.0003604198,0.2366398,0.2115521,0.1154625,0.004426246,0.4282397],"study_design_scores_gemma":[0.0000676645,0.0003677187,0.0003752171,0.00004756676,0.00002742814,0.0004438725,0.0000407876,0.8353994,0.1109218,0.03629117,0.01595449,0.00006290349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04746784,0.0007281265,0.9469481,0.0001537195,0.00006577156,0.0001008559,0.00006570642,0.001877106,0.002592792],"genre_scores_gemma":[0.6428475,0.000572001,0.3498609,0.00009396736,0.00004860293,0.0001462842,0.0001597747,0.0001239134,0.006147184],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001592604,"threshold_uncertainty_score":0.005241573,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03817316571942123,"score_gpt":0.2431296144483664,"score_spread":0.2049564487289452,"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."}}