{"id":"W2046474027","doi":"10.1007/s00778-013-0318-x","title":"Consistency anomalies in multi-tier architectures: automatic detection and prevention","year":2013,"lang":"en","type":"article","venue":"The VLDB Journal","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Consistency (knowledge bases); Computer science; Anomaly detection; Isolation (microbiology); Database transaction; Set (abstract data type); Data mining; Database; Distributed computing; Artificial intelligence; Programming language","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":[0.003576198,0.0006783207,0.001007138,0.003006988,0.0008076833,0.002079629,0.0020933,0.001355735,0.0007172665],"category_scores_gemma":[0.02071556,0.0006908653,0.0005507961,0.002186673,0.0008296196,0.002405793,0.001675058,0.001721138,0.0003384245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009190132,"about_ca_system_score_gemma":0.002357247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003406652,"about_ca_topic_score_gemma":0.005865923,"domain_scores_codex":[0.9932188,0.00101438,0.0006081504,0.001092431,0.003510432,0.0005558304],"domain_scores_gemma":[0.9679357,0.01020362,0.007712883,0.007344904,0.006023142,0.000779603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001631017,0.0006726473,0.4160343,0.0005142884,0.0003467167,0.001087252,0.0007645724,0.05918337,0.08937742,0.01140177,0.008194437,0.4107921],"study_design_scores_gemma":[0.00008068988,0.0003392546,0.04792956,0.00006737489,0.0002307933,0.001871686,0.0003587384,0.8731759,0.05829308,0.01448726,0.003081803,0.00008382606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5713867,0.002327119,0.4081288,0.001014926,0.000328427,0.0002206025,0.0007075186,0.01370274,0.002183099],"genre_scores_gemma":[0.9479831,0.0002240859,0.05054151,0.00009339856,0.00004843601,0.00003049189,0.0004332561,0.0001653124,0.0004802577],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003576198,"threshold_uncertainty_score":0.01891303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0173761358373862,"score_gpt":0.2477361317347878,"score_spread":0.2303599958974016,"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."}}