{"id":"W2976839820","doi":"10.22215/etd/2013-10750","title":"Distributed Multiple Access for the Uplink of Multi-cell OFDMA Networks","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Ministero dello Sviluppo Economico; Ontario Ministry of Economic Development and Innovation","keywords":"Computer science; Computer network; Scheduling (production processes); Telecommunications link; Wireless network; Duplex (building); Quality of service; Cellular network; Overhead (engineering); Wireless; Distributed computing; Engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000566388,0.0003190907,0.0003518582,0.00005681963,0.00008506096,0.00005514574,0.0004633472,0.000379569,0.0001189707],"category_scores_gemma":[0.00003646619,0.0002464007,0.000139484,0.0002448092,0.00001819135,0.0001900323,0.00002576384,0.0002588779,0.000003908524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004519813,"about_ca_system_score_gemma":0.00001574612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003659933,"about_ca_topic_score_gemma":0.0001845938,"domain_scores_codex":[0.9989052,0.000009543638,0.0004536044,0.0002227784,0.0001110251,0.0002978313],"domain_scores_gemma":[0.9987082,0.0004398192,0.0002079489,0.0003369642,0.0002591347,0.00004787846],"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":[0.00002268051,0.00002842325,0.00007949208,0.0002831569,0.00007215097,8.516943e-8,0.00003950076,0.9813234,0.0001723109,0.00001886823,0.003435661,0.01452422],"study_design_scores_gemma":[0.0006433815,0.000008605879,0.0006036456,0.00008291291,0.00008373937,7.558452e-8,0.00009040831,0.9933482,0.004109544,0.000008042292,0.0007500584,0.0002713868],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002220311,0.003101117,0.9913254,0.000008209618,0.001278988,0.001486665,0.00009330737,0.0002692488,0.0002167652],"genre_scores_gemma":[0.9371824,0.00603014,0.02671359,0.00002658091,0.0005216533,0.002333676,0.01807253,0.0004006444,0.008718755],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9646118,"threshold_uncertainty_score":0.9999988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01466865874024821,"score_gpt":0.2554707963518346,"score_spread":0.2408021376115863,"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."}}