{"id":"W2163520627","doi":"","title":"On Tackling Virtual Data Center Embedding Problem","year":2013,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Center (category theory); Computer science; Embedding; Data center; Human–computer interaction; Artificial intelligence; Computer 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":[0.001184552,0.001213079,0.00137916,0.0007309933,0.0008363927,0.001781364,0.001601978,0.002323798,0.008006194],"category_scores_gemma":[0.008517216,0.0005752101,0.0005949147,0.001380542,0.001148005,0.004867284,0.002864555,0.002219865,0.0005895167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006341327,"about_ca_system_score_gemma":0.0007407177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001740154,"about_ca_topic_score_gemma":0.001194801,"domain_scores_codex":[0.9992185,0.00034694,0.00002330925,0.0001912397,0.0001127478,0.0001072277],"domain_scores_gemma":[0.9961301,0.002893144,0.0002140613,0.0002879257,0.000294736,0.0001799487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002683359,0.0001875347,0.00101944,0.0005988826,0.0001046602,0.0002349255,0.0002114635,0.5466857,0.002126904,0.3106855,0.02355338,0.1143232],"study_design_scores_gemma":[0.00001479802,0.00004084519,0.00009743879,0.00003050331,0.00001832885,0.00006485835,0.00007765157,0.8524845,0.0004223307,0.1430603,0.003679638,0.000008850171],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03422927,0.001822248,0.948438,0.002253171,0.0004156205,0.00006062146,0.0001531156,0.0002460089,0.01238194],"genre_scores_gemma":[0.6639454,0.002953499,0.302046,0.0008858955,0.0009343941,0.0001804496,0.0005848469,0.0003797706,0.02808972],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008006194,"threshold_uncertainty_score":0.02678335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02289889605861275,"score_gpt":0.2501054313199239,"score_spread":0.2272065352613111,"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."}}