{"id":"W2112880133","doi":"10.1109/icpads.2010.67","title":"Multi-consistency Data Replication","year":2010,"lang":"en","type":"article","venue":"","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Consistency model; Computer science; Eventual consistency; Distributed computing; Sequential consistency; Replication (statistics); Correctness; Weak consistency; Replica; Causal consistency; Linearizability; Strong consistency; Consistency (knowledge bases); Scalability; Serializability; Data consistency; Algorithm; Transaction processing; Programming language; Operating system; Estimator; Database transaction; Distributed transaction","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":[0.0003368222,0.00005518608,0.00006664081,0.00001835365,0.00007010742,0.0001219424,0.001759153,0.00003994025,0.00002133733],"category_scores_gemma":[0.00009665979,0.00004495212,0.00001469103,0.0001539966,0.00001956935,0.0005596965,0.0003311288,0.00009628148,0.0002109996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003113391,"about_ca_system_score_gemma":0.0000355846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008150614,"about_ca_topic_score_gemma":0.0001245536,"domain_scores_codex":[0.9991414,0.00001099193,0.0001509449,0.0004737116,0.0001061124,0.0001168388],"domain_scores_gemma":[0.9958183,0.00001830965,0.00004774999,0.003998104,0.00006183445,0.00005571889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001458175,0.0002622268,0.003486598,0.00001715108,0.00001662396,0.000009735516,0.0001709371,0.000003419531,0.07470507,0.5313523,0.05910273,0.3308718],"study_design_scores_gemma":[0.0003097677,0.00001016482,0.0216265,0.000005987535,0.000002160225,0.00004294292,0.00001196084,0.5377111,0.001322731,0.0004151468,0.4383454,0.000196132],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003583145,0.00002947024,0.9820541,0.001313789,0.0006468148,0.0001054255,0.00001979576,0.0002414028,0.01200613],"genre_scores_gemma":[0.7646984,0.000001711006,0.233287,0.0002421816,0.00005456419,0.00000742064,0.0000387482,0.000002943349,0.001667033],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7611153,"threshold_uncertainty_score":0.3268974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05702123638455012,"score_gpt":0.3108324336379529,"score_spread":0.2538111972534028,"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."}}