{"id":"W2105147661","doi":"10.1109/icpads.2007.4447751","title":"On the relative value of local scheduling versus routing in parallel server systems","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":"McMaster University","funders":"","keywords":"Computer science; Server; Scheduling (production processes); Routing (electronic design automation); Distributed computing; Computer network; Parallel computing; Mathematical optimization; Mathematics","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":[0.001142256,0.00007726681,0.0001140484,0.00004232627,0.00005329829,0.00002927353,0.0003474749,0.00005072151,0.000005056284],"category_scores_gemma":[0.00005101677,0.00005073111,0.00003946531,0.0002829631,0.00003607355,0.0001398741,0.00005561013,0.0001720137,0.00002256828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004593946,"about_ca_system_score_gemma":0.00003448211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008602151,"about_ca_topic_score_gemma":0.00005020253,"domain_scores_codex":[0.999074,0.0000921723,0.0002460892,0.0001745497,0.0002092059,0.0002039823],"domain_scores_gemma":[0.9983237,0.001277898,0.00007971466,0.0002397715,0.00004448299,0.00003441332],"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":[0.00003799762,0.00001378844,0.0001165473,0.000001488487,0.00001026174,0.000004117546,0.0001637422,0.1627723,0.000001863427,0.8276513,0.00001472297,0.009211933],"study_design_scores_gemma":[0.0007466692,0.0000679672,0.000865893,0.00006082557,0.000002765656,0.000001067995,0.0003954849,0.9966805,0.00002583429,0.001055093,0.00002823844,0.00006969092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09730786,0.00007245309,0.8941066,0.0004614309,0.0003907875,0.0001261822,7.05277e-8,0.00004539797,0.007489248],"genre_scores_gemma":[0.9960715,0.000001461212,0.003605261,0.0001278895,0.00003997409,0.000003756683,1.393775e-7,0.000003262639,0.0001467087],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8987637,"threshold_uncertainty_score":0.2068755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02024287197767657,"score_gpt":0.2441677982138688,"score_spread":0.2239249262361923,"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."}}