{"id":"W2332709574","doi":"10.1109/twc.2016.2547378","title":"Multimedia Content Delivery in Millimeter Wave Home Networks","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Resource allocation; Bandwidth (computing); Heuristic; Convex optimization; Wireless; Mathematical optimization; Optimization problem; Wireless network; Integer programming; Computer network; Distributed computing; Algorithm; Telecommunications; Regular polygon; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005903384,0.0005144714,0.0007540244,0.0005267971,0.00055083,0.00105878,0.0009318348,0.0007248112,0.001068847],"category_scores_gemma":[0.001587813,0.0002888355,0.0002837754,0.001014858,0.0004107916,0.001151445,0.0008678723,0.0006184737,0.000227075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001388904,"about_ca_system_score_gemma":0.0005570751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002621324,"about_ca_topic_score_gemma":0.001977912,"domain_scores_codex":[0.9995684,0.0001703653,0.00001473076,0.00005738111,0.0001118229,0.0000772514],"domain_scores_gemma":[0.9995506,0.0002731906,0.00005199861,0.00003471143,0.00006428803,0.00002515151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002668482,0.0001398199,0.0006066124,0.000221917,0.0000389236,0.0003427968,0.0001765232,0.7950532,0.01089577,0.04231822,0.006808398,0.143131],"study_design_scores_gemma":[0.000006574412,0.00001817876,0.00008211533,0.000005691888,0.000006272833,0.00003829918,0.00002742763,0.9916409,0.00170723,0.005208137,0.00125553,0.000003654441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0436883,0.001359869,0.9478648,0.000361183,0.00005944372,0.00008964723,0.00008576614,0.0004387607,0.006052265],"genre_scores_gemma":[0.7955073,0.001650209,0.1979617,0.0001700544,0.00009093324,0.0002209989,0.0001721525,0.000117993,0.004108681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002621324,"threshold_uncertainty_score":0.0100773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05816597491839962,"score_gpt":0.2347861389077901,"score_spread":0.1766201639893905,"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."}}