{"id":"W2098857789","doi":"10.1109/jsac.2012.120920","title":"Fair Scheduling and Resource Allocation for Wireless Cellular Network with Shared Relays","year":2012,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Relay; Computer network; Frequency reuse; Scheduling (production processes); Beamforming; Wireless; Base station; Wireless network; Resource allocation; Backhaul (telecommunications); Distributed computing; Telecommunications; Mathematical optimization","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":[0.002298956,0.0007643619,0.0008979843,0.0005461554,0.001007085,0.001173747,0.001369869,0.0006766575,0.001450276],"category_scores_gemma":[0.004975799,0.0003161923,0.0003195123,0.0008049449,0.001125985,0.00131079,0.001013231,0.0005475644,0.0002311516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002522791,"about_ca_system_score_gemma":0.002321773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005904717,"about_ca_topic_score_gemma":0.007486464,"domain_scores_codex":[0.9988874,0.0004601998,0.00003590534,0.0001724593,0.0002288515,0.0002151463],"domain_scores_gemma":[0.99814,0.001132947,0.0001702495,0.0001918686,0.0002385428,0.0001262986],"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":[0.0001904415,0.0000492497,0.0003215591,0.00004763077,0.0000308612,0.00009252549,0.00008030939,0.9289261,0.002132388,0.04186742,0.001235023,0.0250266],"study_design_scores_gemma":[0.00001482123,0.00002305807,0.00005909034,0.000002357796,0.000005946931,0.00001311023,0.00001455556,0.9879892,0.0003231737,0.01115409,0.0003955297,0.000005017694],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06739419,0.0007305346,0.9270045,0.0002437654,0.0001075149,0.0001137307,0.00008491432,0.0001950249,0.004125824],"genre_scores_gemma":[0.9493436,0.0002657337,0.04877818,0.00004657578,0.00005957116,0.00009805948,0.00003375755,0.00002467707,0.001349882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005904717,"threshold_uncertainty_score":0.01830423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04900163063075268,"score_gpt":0.2869889880999333,"score_spread":0.2379873574691806,"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."}}