{"id":"W2126427712","doi":"10.1109/pimrc.2006.254227","title":"An Agent System to Manage Mobile Connections in a Distributed Base Station Scheme","year":2006,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Base station; Scalability; Distributed computing; Computer network; Protocol (science); Resource allocation; Simple (philosophy); Scheme (mathematics); Node (physics); Mobile agent; Macro; Resource management (computing); Engineering; Database","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009690145,0.0004321544,0.0004996617,0.0004968035,0.001031504,0.001508223,0.00140461,0.0008017272,0.003049315],"category_scores_gemma":[0.001514777,0.0002470913,0.0002948385,0.0003945378,0.0006600124,0.001407517,0.001444717,0.001092316,0.001001317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004945806,"about_ca_system_score_gemma":0.000734681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001019306,"about_ca_topic_score_gemma":0.00112807,"domain_scores_codex":[0.9996241,0.0001153935,0.00003901398,0.00005909193,0.0001205712,0.0000417578],"domain_scores_gemma":[0.9993448,0.0001633248,0.00006641698,0.0001773616,0.0001113381,0.0001366264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006018126,0.0005183041,0.002553034,0.0002736044,0.0002083659,0.001133699,0.001198662,0.09713586,0.06009699,0.5850133,0.01084713,0.2404193],"study_design_scores_gemma":[0.0003151855,0.0004575342,0.0005240276,0.00003994429,0.000132735,0.0003408026,0.0001015007,0.8473954,0.01384696,0.05221688,0.0845568,0.00007228551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02635904,0.0002862515,0.9631623,0.000257259,0.0002199613,0.0002939921,0.00004311621,0.001836813,0.007541163],"genre_scores_gemma":[0.4967224,0.0003463609,0.4871807,0.0001633297,0.0001966616,0.0007513101,0.0001775617,0.0001020133,0.01435975],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003049315,"threshold_uncertainty_score":0.01020098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02462539309067619,"score_gpt":0.2812417462211027,"score_spread":0.2566163531304265,"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."}}