{"id":"W3031483518","doi":"10.1109/icde48307.2020.00123","title":"DynaMast: Adaptive Dynamic Mastering for Replicated Systems","year":2020,"lang":"en","type":"article","venue":"","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Scalability; Bottleneck; Distributed computing; Replica; Benchmark (surveying); Database transaction; Protocol (science); Metadata; Distributed database; Transaction processing; Database; Atomicity; Operating system; Embedded system","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":[0.001725835,0.0005440615,0.0006842065,0.0005935291,0.0008572461,0.001528507,0.002752889,0.0006154223,0.002883009],"category_scores_gemma":[0.004992213,0.000593425,0.0004413388,0.0006930924,0.0007783051,0.002417396,0.002931237,0.001338933,0.00105851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008528852,"about_ca_system_score_gemma":0.001257899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001399282,"about_ca_topic_score_gemma":0.001640602,"domain_scores_codex":[0.9986858,0.000293728,0.0001230275,0.0001964106,0.0005618464,0.0001393249],"domain_scores_gemma":[0.9974399,0.0006508967,0.0002050055,0.001070598,0.0004448224,0.0001888673],"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":[0.001846381,0.0003742627,0.005649013,0.0009332484,0.0002471077,0.0007660689,0.0009424584,0.2455196,0.1136482,0.08605859,0.06072839,0.4832867],"study_design_scores_gemma":[0.0002645723,0.0002200637,0.0005987611,0.00003910828,0.00004775771,0.0003962643,0.00009943808,0.9003708,0.03190484,0.02893508,0.03704734,0.00007594588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02319446,0.0006961599,0.9473655,0.0003508692,0.0001641274,0.0002641026,0.0003796758,0.02307869,0.004506378],"genre_scores_gemma":[0.6222831,0.0006971413,0.3648634,0.0003085281,0.0001679377,0.0006203812,0.001325798,0.00208588,0.007647805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002883009,"threshold_uncertainty_score":0.009644628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03435363512453012,"score_gpt":0.2463280984179234,"score_spread":0.2119744632933933,"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."}}