{"id":"W2786649087","doi":"10.1109/vtcfall.2017.8288144","title":"Energy Efficient Packet Transmission Strategies for Wireless Body Area Networks with Rechargeable Sensors","year":2017,"lang":"en","type":"article","venue":"","topic":"Wireless Body Area Networks","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Network packet; Queueing theory; Markov chain; Transmission (telecommunications); Markov process; Channel (broadcasting); Efficient energy use; Energy (signal processing); Computer network; Wireless; Wireless sensor network; Provisioning; Maximization; Body area network; Mathematical optimization; Real-time computing; Distributed computing; Telecommunications; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001656508,0.0003395551,0.000343961,0.0000594805,0.0004670678,0.0003410102,0.0003696711,0.0002217677,0.00007208196],"category_scores_gemma":[0.000003256672,0.0002661857,0.00009142684,0.00007522452,0.00008632371,0.0002413096,0.00002661957,0.000186354,0.000003182264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005668143,"about_ca_system_score_gemma":0.00003814857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000772679,"about_ca_topic_score_gemma":0.0001028915,"domain_scores_codex":[0.9985525,0.00001844503,0.0002473,0.0003471132,0.0001923378,0.0006422818],"domain_scores_gemma":[0.9988775,0.00009310173,0.0000754416,0.0006956101,0.00007780237,0.0001805851],"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":[0.00009525473,0.0000323698,0.00006098059,0.00005789877,0.00007016379,0.0000140343,0.00008656683,0.9776572,0.00106234,0.004881421,0.004896746,0.01108501],"study_design_scores_gemma":[0.0007257461,0.00008366677,0.0001346408,0.0001613136,0.0000311461,0.000009117224,0.0001637466,0.9871842,0.005413763,0.0001649843,0.005510672,0.0004170277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1540786,0.0001826717,0.8264678,0.00008727338,0.0003267863,0.0002885622,0.000009308019,0.0006065487,0.01795249],"genre_scores_gemma":[0.9962186,0.0001609652,0.002210333,0.00002372972,0.0002350031,0.0001006499,0.00003593828,0.0001100275,0.0009047861],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.84214,"threshold_uncertainty_score":0.999979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01270943644997747,"score_gpt":0.2139173514695168,"score_spread":0.2012079150195393,"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."}}