{"id":"W1504348028","doi":"10.1002/wcm.2339","title":"Resource allocation with interference mitigation in femtocellular networks","year":2012,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Femtocell; Computer science; Benchmark (surveying); Software deployment; Telecommunications link; Computer network; Interference (communication); Resource allocation; Cellular network; Scheme (mathematics); Wireless ad hoc network; Frequency allocation; Telecommunications; Wireless; Base station","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":[0.0002137735,0.0001095645,0.0001242881,0.00007860039,0.0001197359,0.00003042182,0.0001893962,0.00005626065,0.000001204951],"category_scores_gemma":[0.00000458132,0.0001135842,0.00001030287,0.0002516767,0.00005673753,0.0002187767,0.0001016853,0.000183978,0.000001538985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006553415,"about_ca_system_score_gemma":0.000005416257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001405327,"about_ca_topic_score_gemma":0.00002549481,"domain_scores_codex":[0.9993543,0.00006612028,0.0002380507,0.0001003129,0.00004490079,0.0001963386],"domain_scores_gemma":[0.9992545,0.0001082292,0.00006130804,0.0004861644,0.00003780349,0.00005198571],"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":[0.000003037256,0.00003756177,0.01282137,0.00004221098,0.000009900099,1.609164e-7,0.002140301,0.9190825,0.0007170324,0.001554252,0.00001085897,0.06358082],"study_design_scores_gemma":[0.0001776839,0.00001672553,0.001182238,0.0002001403,0.000005293829,0.000007527112,0.0007142574,0.9965943,0.0001914719,0.000006293789,0.000765591,0.0001385313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2905649,0.003142583,0.7050884,0.00001852802,0.00003757937,0.0002946763,6.196024e-7,0.0001477772,0.0007049997],"genre_scores_gemma":[0.9877999,0.0003378027,0.01164403,0.00001101103,0.00003774306,0.00007680226,0.00005782917,0.0000258625,0.000008969136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.697235,"threshold_uncertainty_score":0.463183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01105905293911986,"score_gpt":0.2255531001782468,"score_spread":0.214494047239127,"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."}}