{"id":"W1571333849","doi":"10.1109/inm.2015.7140356","title":"Kaleidoscope: Real-time content delivery in software defined infrastructures","year":2015,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Provisioning; Cloud computing; Computer science; Software-defined networking; Kaleidoscope; Virtualization; Content delivery network; Software deployment; Quality of service; Content management; Resource allocation; Software as a service; Multimedia; Software; Computer network; Server; Software development; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003005932,0.0002103815,0.0002780107,0.0001495616,0.00005163548,0.0001494163,0.0008120144,0.0001163284,0.0000889024],"category_scores_gemma":[0.0002011356,0.0001713555,0.00006198577,0.0005179506,0.00004464294,0.0004522481,0.000402832,0.0001585149,0.0002595679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009503052,"about_ca_system_score_gemma":0.0001820734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001113396,"about_ca_topic_score_gemma":0.0001649448,"domain_scores_codex":[0.9983675,0.00007588336,0.0003304869,0.0004446577,0.0003396885,0.0004418205],"domain_scores_gemma":[0.9987175,0.0002096415,0.00007721492,0.0005996408,0.0001532914,0.0002427451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002290059,0.0003495426,0.3373339,0.00004372665,0.00009480021,0.0004105191,0.002598434,0.009813329,0.001377181,0.05380793,0.4285095,0.1654321],"study_design_scores_gemma":[0.01344012,0.001661471,0.7271623,0.0003867235,0.00005010827,0.0002684051,0.000399061,0.1276127,0.003087177,0.09747774,0.02482997,0.003624192],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5951915,0.0009877341,0.3867452,0.00116849,0.001384187,0.0005810867,0.000009982703,0.001897996,0.01203391],"genre_scores_gemma":[0.5411004,0.0001048475,0.4544918,0.002155644,0.0001870512,0.00003980011,0.00002166607,0.00003644203,0.001862318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4036795,"threshold_uncertainty_score":0.6987675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03601653211123421,"score_gpt":0.2324472897808513,"score_spread":0.1964307576696171,"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."}}