{"id":"W2122715073","doi":"10.1109/nca.2007.38","title":"Scalable Communication for High Performance and Inexpensive Reliable QoS using Relaxed Recovery","year":2007,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Backup; Scalability; Computer science; Computer network; Quality of service; Distributed computing; Overhead (engineering); Broadcasting (networking); Path (computing); Routing (electronic design automation); High availability; Database","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":[0.0005439479,0.00008578332,0.0001187207,0.00005525833,0.000247442,0.00008836002,0.0002774092,0.00006031265,0.000006411819],"category_scores_gemma":[0.00002649474,0.00007953035,0.00001929348,0.0001765045,0.00003504842,0.0005804133,0.0001022018,0.00008065359,0.000007357537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004006031,"about_ca_system_score_gemma":0.00003710149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005160709,"about_ca_topic_score_gemma":0.00002360067,"domain_scores_codex":[0.9992533,0.00001680066,0.0001977231,0.0002090335,0.00009506176,0.000228105],"domain_scores_gemma":[0.9990686,0.0002419698,0.00007860216,0.0003945988,0.0001577439,0.00005852252],"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":[0.0002362216,0.00009376043,0.002661023,0.00004774499,0.00005241543,0.000002968539,0.0003887058,0.01205865,0.001499634,0.1727936,0.01496794,0.7951974],"study_design_scores_gemma":[0.00107272,0.0001628777,0.00250498,0.00006040241,0.00001234152,0.00001769334,0.00006256632,0.9858479,0.001546247,0.001760028,0.006730132,0.0002220844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3165044,0.0002554293,0.6806598,0.0004829827,0.0002956463,0.0002325566,3.722413e-7,0.0001085575,0.001460299],"genre_scores_gemma":[0.8379431,0.0001149294,0.1600072,0.0005364526,0.0000665773,0.00001004643,0.000002378053,0.000006120202,0.001313235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9737893,"threshold_uncertainty_score":0.3243154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01532344069833709,"score_gpt":0.2312214284034182,"score_spread":0.2158979877050811,"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."}}