{"id":"W2120095495","doi":"10.1109/glocom.2010.5683278","title":"Hierarchical Competition in Femtocell-Based Cellular Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Femtocell; Stackelberg competition; Macrocell; Nash equilibrium; Computer science; Game theory; Telecommunications link; Cellular network; Strategy; Best response; Base station; Potential game; Computer network; Mathematical optimization; Mathematical economics; Mathematics","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":[0.00007888618,0.00008606398,0.00009349456,0.00007630845,0.00001738252,0.00001369308,0.00006323787,0.0001015704,0.0001790765],"category_scores_gemma":[0.000008877895,0.00008946759,0.0000203122,0.0001509935,0.00001729782,0.00007065833,0.000006639431,0.0002835734,0.0000307043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002437356,"about_ca_system_score_gemma":0.000005850715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008988541,"about_ca_topic_score_gemma":0.0001463894,"domain_scores_codex":[0.9995115,0.00001227816,0.0001602347,0.0001030416,0.0000535894,0.0001594043],"domain_scores_gemma":[0.999741,0.00003711458,0.00001132784,0.0001494223,0.0000144004,0.00004670766],"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":[0.000002365225,0.00001062745,0.0005782528,0.0000131976,0.000001150173,0.000003482929,0.00001024011,0.9820372,0.01428829,0.002663412,0.00008359892,0.000308215],"study_design_scores_gemma":[0.0002852632,0.000006311987,0.0002262058,0.00001111742,0.000001168986,9.901909e-7,0.000005080401,0.9933839,0.005148488,0.0001243988,0.0006989742,0.0001080302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02647923,0.00002083974,0.9591787,0.00002713327,0.0004216436,0.0001560247,7.153848e-7,0.0003110919,0.01340459],"genre_scores_gemma":[0.9791927,0.000002563127,0.0204985,0.00003015876,0.0001070237,0.00001958219,0.00003334653,0.00002512961,0.0000909442],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9527135,"threshold_uncertainty_score":0.3648382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004835708850707638,"score_gpt":0.1932075696876318,"score_spread":0.1883718608369242,"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."}}