{"id":"W2521346046","doi":"10.1002/wcm.2718","title":"A distributed battery recovery aware topology control algorithm for wireless sensor networks","year":2016,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Wireless sensor network; Topology control; Computer network; Key distribution in wireless sensor networks; Distributed algorithm; Battery (electricity); Topology (electrical circuits); Mobile wireless sensor network; Network topology; Distributed computing; Algorithm; Wireless; Wireless network; Telecommunications; Electrical engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005841214,0.0003530689,0.0005439297,0.0001442795,0.0009299048,0.0002077904,0.001966717,0.0002408249,0.000003491542],"category_scores_gemma":[0.00002771673,0.0002927939,0.0001669927,0.0004035679,0.000394991,0.0002834771,0.001196302,0.0002780363,0.000004539239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001130654,"about_ca_system_score_gemma":0.00006536731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003478508,"about_ca_topic_score_gemma":0.0000201467,"domain_scores_codex":[0.9972647,0.0003992011,0.000662038,0.0007339636,0.0001743737,0.0007656647],"domain_scores_gemma":[0.9935808,0.003201751,0.0003749314,0.002313555,0.0003303305,0.0001986825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000012472,0.00015852,0.0004519502,0.00001438873,0.00008391935,0.000004438324,0.0001232735,0.02470923,0.0004224925,0.006757835,0.0003295349,0.9669319],"study_design_scores_gemma":[0.001415213,0.0001703152,0.0002322485,0.0001902129,0.0000236641,0.00004918121,0.00008188987,0.9915287,0.0001212235,0.0001094894,0.005659161,0.0004187338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02860688,0.0009479956,0.9670807,0.001639552,0.0005197346,0.0006746455,0.00008609812,0.0004012432,0.00004319135],"genre_scores_gemma":[0.9285285,0.0008975766,0.06956182,0.0004078108,0.000196424,0.0002236838,0.00007046231,0.00004183959,0.00007182285],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9668195,"threshold_uncertainty_score":0.9999524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01232862701142147,"score_gpt":0.2482424544839842,"score_spread":0.2359138274725627,"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."}}