{"id":"W2029434191","doi":"10.1109/glocom.2011.6134158","title":"Constrained Energy-Aware AP Placement with Rate Adaptation in WLAN Mesh Networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Quality of service; Energy consumption; Heuristic; Renewable energy; Computer network; Efficient energy use; Wireless mesh network; Distributed computing; Wireless network; Wireless; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001002967,0.0005829714,0.0007379502,0.0005930329,0.0003497069,0.0005788791,0.001220716,0.0007302765,0.0007223168],"category_scores_gemma":[0.00319283,0.0004485439,0.0003223821,0.001013433,0.0004140919,0.0009665991,0.0008040649,0.0004211393,0.0001808278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006164734,"about_ca_system_score_gemma":0.0004873693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002204969,"about_ca_topic_score_gemma":0.002293966,"domain_scores_codex":[0.9994214,0.0003053539,0.0000264717,0.00007389439,0.0001051588,0.00006774835],"domain_scores_gemma":[0.999116,0.0005833195,0.0001288959,0.00007556978,0.00006495383,0.00003129559],"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":[0.00007160661,0.0000256951,0.0004332824,0.00003425486,0.00001748754,0.00005861558,0.00003223551,0.9649813,0.001834812,0.003901835,0.0004339308,0.02817497],"study_design_scores_gemma":[0.000007221975,0.00001759793,0.00007515559,0.000002707177,0.000004271075,0.00001947883,0.000009778388,0.9967501,0.0003381929,0.002557566,0.0002142219,0.000003747719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03827649,0.0005208271,0.9591477,0.0001556752,0.00003236773,0.00004261772,0.0000362162,0.0001984343,0.001589595],"genre_scores_gemma":[0.8325148,0.0006060041,0.1649219,0.00005426107,0.0000534368,0.0001082435,0.0000790523,0.00003933684,0.001623041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002204969,"threshold_uncertainty_score":0.005304277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02946598179568547,"score_gpt":0.2221346690987005,"score_spread":0.192668687303015,"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."}}