{"id":"W2155962735","doi":"10.1109/tmc.2010.229","title":"Adaptive Asynchronous Sleep Scheduling Protocols for Delay Tolerant Networks","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Asynchronous communication; Sleep mode; Computer network; Energy consumption; Distributed computing; Efficient energy use; Scalability; Power management; Network packet; Scheduling (production processes); Power consumption; Power (physics)","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":[0.0007318855,0.0004513504,0.0002853489,0.00057672,0.0006270751,0.0006468857,0.001123278,0.0003218404,0.001320115],"category_scores_gemma":[0.001583059,0.0001606844,0.0002312437,0.000514622,0.0004896477,0.0009679288,0.0006042263,0.0006365296,0.0002221482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006096285,"about_ca_system_score_gemma":0.000591101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006042654,"about_ca_topic_score_gemma":0.001083911,"domain_scores_codex":[0.999656,0.00009905057,0.00004096574,0.00005529016,0.0001218163,0.00002691651],"domain_scores_gemma":[0.9992431,0.0003234594,0.0001243163,0.0001168018,0.0001491501,0.00004315404],"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":[0.0005415163,0.0001885893,0.001292507,0.000730222,0.000108641,0.0003273631,0.000738519,0.176653,0.07820061,0.3463905,0.006935297,0.3878933],"study_design_scores_gemma":[0.0001736108,0.0004394082,0.0004673548,0.00008216443,0.0001117544,0.0004362549,0.0002114548,0.8396121,0.02589921,0.08476686,0.04773185,0.00006799216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02344597,0.001376005,0.9695467,0.0002337196,0.0003169043,0.0001964374,0.00005012157,0.000449256,0.0043849],"genre_scores_gemma":[0.7175286,0.001979416,0.2738825,0.0003407428,0.0003593932,0.0006035446,0.0001992709,0.00009336932,0.005013099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001320115,"threshold_uncertainty_score":0.004423141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207387829873364,"score_gpt":0.2764403257347331,"score_spread":0.2543664474359995,"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."}}