{"id":"W2025349149","doi":"10.1109/tcomm.2015.2404440","title":"MINTED: &lt;italic&gt;M&lt;/italic&gt;ulticast &lt;italic&gt;VI&lt;/italic&gt;rtual &lt;italic&gt;N&lt;/italic&gt;e&lt;italic&gt;T&lt;/italic&gt;work &lt;italic&gt;E&lt;/italic&gt;mbedding in Cloud Data Centers With &lt;italic&gt;D&lt;/italic&gt;elay Constraints","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Qatar National Research Fund","keywords":"Multicast; Computer science; Computer network; Unicast; Quality of service","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000984279,0.001552588,0.001021701,0.001083559,0.001957051,0.007881642,0.001947446,0.002913006,0.7696226],"category_scores_gemma":[0.0028643,0.0005617068,0.0008047509,0.001828471,0.001558063,0.004603214,0.004115955,0.002348569,0.6639788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003424122,"about_ca_system_score_gemma":0.00212359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006167521,"about_ca_topic_score_gemma":0.006593516,"domain_scores_codex":[0.9987007,0.0001650945,0.00006817252,0.000512358,0.0003071029,0.000246397],"domain_scores_gemma":[0.9979236,0.0003889438,0.0001633765,0.0004013834,0.0007281886,0.0003945464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003302736,0.0001283814,0.001234496,0.0005037738,0.00002414885,0.000444441,0.0003528348,0.002020445,0.004553637,0.05531417,0.6590045,0.2760889],"study_design_scores_gemma":[0.00001272543,0.00002331164,0.0004162784,0.0000869078,0.000005225051,0.0001162733,0.0001720351,0.001767162,0.001043979,0.004664225,0.9916802,0.00001171973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.005242625,0.002297936,0.01539345,0.01754562,0.01321735,0.0003357716,0.004215879,0.002945257,0.9388062],"genre_scores_gemma":[0.01802118,0.001204716,0.002499418,0.001121114,0.0008420569,0.00008883522,0.001662687,0.001119876,0.9734402],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7696226,"threshold_uncertainty_score":0.3286054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05337180103299812,"score_gpt":0.2837657976359783,"score_spread":0.2303939966029802,"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."}}