{"id":"W2013001527","doi":"10.1155/2009/512865","title":"OFDMA-Based Medium Access Control for Next-Generation WLANs","year":2009,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Qatar Foundation","keywords":"Computer science; Computer network; Access control; Media access control; PHY; Random access; Orthogonal frequency-division multiple access; Throughput; Frequency-division multiple access; Orthogonal frequency-division multiplexing; Channel access method; Scalability; Wireless; Time division multiple access; Multiple Access with Collision Avoidance for Wireless; Physical layer; Channel (broadcasting); Wireless network; Wi-Fi array; Telecommunications","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":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0009857563,0.0002177769,0.0003003328,0.0001469094,0.00134811,0.001498842,0.002118565,0.0001034693,0.000004175306],"category_scores_gemma":[0.00001307519,0.0001879103,0.0001229585,0.0003520258,0.00006090539,0.000744715,0.0001216301,0.000491147,0.000001283692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004778939,"about_ca_system_score_gemma":0.0001089757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000303821,"about_ca_topic_score_gemma":0.00001645686,"domain_scores_codex":[0.99825,0.0003423345,0.0004981104,0.0002738216,0.0002500405,0.0003856937],"domain_scores_gemma":[0.9975674,0.0006625428,0.0004129068,0.000956616,0.0002084384,0.0001920993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007346069,0.0002204318,0.0014558,0.00001057355,0.0000456358,0.000005324982,0.0001614985,0.007778925,0.00130398,0.02289125,0.002565952,0.9634871],"study_design_scores_gemma":[0.001432618,0.0003564952,0.001405629,0.00027556,0.00002073362,0.00002293353,0.00000537752,0.9530638,0.0001809753,0.00201808,0.0409564,0.000261382],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0050078,0.003045149,0.9578132,0.03104744,0.0006082268,0.002038809,0.000005004063,0.0001170805,0.0003172686],"genre_scores_gemma":[0.9832185,0.002344183,0.008434066,0.004253345,0.001248915,0.0004558397,0.00001134014,0.00001701467,0.00001677926],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9782107,"threshold_uncertainty_score":0.999952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1195571412195571,"score_gpt":0.3415469372014099,"score_spread":0.2219897959818528,"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."}}