{"id":"W2135010525","doi":"10.1109/tw.2014.011614.131163","title":"Clustering and Resource Allocation for Dense Femtocells in a Two-Tier Cellular OFDMA Network","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":184,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Femtocell; Computer science; Cellular network; Computer network; Orthogonal frequency-division multiple access; Cluster analysis; Resource allocation; Femto-; Distributed computing; Frequency-division multiple access; Wireless network; Orthogonal frequency-division multiplexing; Wireless; Channel (broadcasting); Base station; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002656322,0.0001776046,0.0002114321,0.0001613689,0.0002794287,0.00003995049,0.0002901614,0.0000865191,0.000004215514],"category_scores_gemma":[0.000005588384,0.0002174422,0.00004941281,0.0003196528,0.00006373012,0.0001686245,0.000005126218,0.0002485359,0.000005766399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001084705,"about_ca_system_score_gemma":0.00001085426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004305661,"about_ca_topic_score_gemma":0.000947828,"domain_scores_codex":[0.9989963,0.0001182276,0.0003672926,0.0001972021,0.00007518903,0.000245842],"domain_scores_gemma":[0.9985288,0.0003947688,0.00006145152,0.0008899632,0.0000572274,0.00006777715],"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":[0.00001371867,0.000042456,0.00002355356,0.00005872302,0.00001970438,8.383675e-8,0.0004093774,0.9721298,0.005295115,0.0002826714,0.00003858116,0.02168621],"study_design_scores_gemma":[0.0006966554,0.00002245825,0.00002381997,0.0001634996,0.00002892606,0.000002049511,0.00008376147,0.9920068,0.004535143,0.0001090771,0.002112249,0.0002155627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01202099,0.000358918,0.9859203,0.0002221431,0.0001633429,0.0007005753,0.00001546693,0.0002421363,0.00035611],"genre_scores_gemma":[0.9677582,0.0004261182,0.03077989,0.00004976802,0.00004500143,0.0007238843,0.00002284011,0.00006905241,0.0001252447],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9557372,"threshold_uncertainty_score":0.8867034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673242376324071,"score_gpt":0.2450569857486859,"score_spread":0.2283245619854452,"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."}}