{"id":"W4386768673","doi":"10.14778/3611540.3611542","title":"Taurus MM: Bringing Multi-Master to the Cloud","year":2023,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Cloud computing; Distributed computing; Computer network; Protocol (science); Node (physics); Operating system; Engineering","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":[0.001497212,0.000665052,0.0007994503,0.0008928887,0.0009687764,0.00212323,0.003298216,0.0005757682,0.003345984],"category_scores_gemma":[0.003714812,0.0006357454,0.0004852083,0.001193005,0.0006956669,0.00369718,0.003644723,0.00152346,0.001047979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008722321,"about_ca_system_score_gemma":0.002252696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004325136,"about_ca_topic_score_gemma":0.004552045,"domain_scores_codex":[0.9983558,0.0002217696,0.0001133328,0.0003624124,0.000677158,0.0002694874],"domain_scores_gemma":[0.996965,0.0002992108,0.000246202,0.001615353,0.0004113688,0.0004628672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002847934,0.0005541693,0.01241404,0.0002964014,0.0002696333,0.0005454331,0.0007439983,0.04208339,0.07657509,0.04254168,0.06503579,0.7560925],"study_design_scores_gemma":[0.0009783981,0.001346514,0.00568509,0.00006683479,0.0002128998,0.0009860436,0.000621817,0.7135497,0.1288527,0.02734241,0.120153,0.0002045439],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1289909,0.001620724,0.8018354,0.0008439635,0.0008423859,0.000489509,0.0005674831,0.05304257,0.01176704],"genre_scores_gemma":[0.5986301,0.0004932124,0.3887956,0.0003973206,0.0003079644,0.0001802687,0.0009167672,0.00150425,0.008774516],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004325136,"threshold_uncertainty_score":0.01119345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02720882880582502,"score_gpt":0.2355862427393772,"score_spread":0.2083774139335522,"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."}}