{"id":"W2146234960","doi":"10.1002/cpe.1791","title":"A MapReduce‐supported network structure for data centers","year":2011,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Data structure; Tree (set theory); Network structure; Tree structure; Big data; Data center; Distributed computing; Data mining; Computer network; Operating system","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":[0.0006297049,0.0001949458,0.0002650303,0.000488864,0.0008824907,0.001053506,0.00103865,0.0004260791,0.002101501],"category_scores_gemma":[0.001156589,0.0001736133,0.000256386,0.0005806329,0.0006019036,0.001648147,0.001331395,0.0005107348,0.0005012099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009896754,"about_ca_system_score_gemma":0.0009541529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001541075,"about_ca_topic_score_gemma":0.002253817,"domain_scores_codex":[0.9996579,0.00009444497,0.00002487685,0.00007358785,0.00009949687,0.00004969421],"domain_scores_gemma":[0.9992719,0.0001191991,0.00007374621,0.0002000573,0.0002395595,0.00009548932],"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":[0.000543459,0.0002404075,0.004232221,0.0003650103,0.00006569423,0.0003803313,0.0004551166,0.2823547,0.03205268,0.4816627,0.02109252,0.1765552],"study_design_scores_gemma":[0.00005270033,0.0001959217,0.001185918,0.00004014877,0.00002648724,0.0003649848,0.0002186281,0.8006407,0.01444829,0.1375073,0.04526587,0.00005307837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09573866,0.000313337,0.889988,0.0007641815,0.000136081,0.0001724385,0.0003711591,0.00111274,0.01140341],"genre_scores_gemma":[0.7394552,0.0002193166,0.2561827,0.0001322285,0.00006200313,0.0001661481,0.0004090363,0.00007216501,0.003301248],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002101501,"threshold_uncertainty_score":0.007180631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06795627963350627,"score_gpt":0.3241512469748351,"score_spread":0.2561949673413288,"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."}}