{"id":"W2114133384","doi":"10.1109/tce.2007.381704","title":"Message Replication and Consumer Database Synchronization Algorithms and System for Highly Available High Performance Intelligent Networks","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Consumer Electronics","topic":"Distributed systems and fault tolerance","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Computer science; Replication (statistics); Asynchronous communication; Distributed computing; High availability; Synchronization (alternating current); Distributed database; Fault tolerance; Service (business); Data synchronization; Computer network; Wireless sensor network","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":[0.001951213,0.0003205384,0.0004598857,0.0007269277,0.000868772,0.001156826,0.001898379,0.0007981254,0.003286803],"category_scores_gemma":[0.004074632,0.0002289302,0.0003193729,0.0007978179,0.0006422899,0.00185508,0.0009254924,0.000871984,0.0009209811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184404,"about_ca_system_score_gemma":0.001362275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00199544,"about_ca_topic_score_gemma":0.001838562,"domain_scores_codex":[0.9987888,0.0003435296,0.0000623176,0.0002468777,0.0004882769,0.00007026175],"domain_scores_gemma":[0.9984285,0.0004278283,0.0001705761,0.0004115103,0.0004810988,0.00008059858],"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":[0.00113571,0.0002768651,0.003066229,0.0002500416,0.0001195894,0.0003429326,0.0008086489,0.1213744,0.04486628,0.3730219,0.01860943,0.436128],"study_design_scores_gemma":[0.0001735773,0.0001918559,0.0007591753,0.0000169174,0.00005322978,0.0002756311,0.00009991117,0.9202565,0.02167901,0.03576889,0.02067214,0.00005314588],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.022648,0.0003108754,0.9712266,0.0003547772,0.0001165787,0.0001058606,0.00003463199,0.0017812,0.003421537],"genre_scores_gemma":[0.469545,0.0002866831,0.5168012,0.0002021351,0.0001957579,0.0003281526,0.000203766,0.0001980276,0.01223935],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003286803,"threshold_uncertainty_score":0.01099545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01297973230207034,"score_gpt":0.2380456360073932,"score_spread":0.2250659037053229,"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."}}