{"id":"W2564538528","doi":"10.1109/nbis.2016.74","title":"EEORS: Energy Efficient Optimal Relay Selection Protocol for Underwater WSNs","year":2016,"lang":"en","type":"article","venue":"","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Alberta","funders":"","keywords":"Relay; Relay channel; Network packet; Computer network; Link Access Procedure for Frame Relay; Wireless sensor network; Sink (geography); Computer science; Node (physics); Efficient energy use; Transmission (telecommunications); Wireless; Engineering; Telecommunications; Electrical engineering; Power (physics); Geography; 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":[0.0006044734,0.0006308756,0.0007488707,0.0006349237,0.0005039782,0.0004251864,0.001275974,0.0004318717,0.0006478528],"category_scores_gemma":[0.001329513,0.0002092702,0.0003487836,0.0005826059,0.0004333123,0.001295743,0.001353726,0.0004999659,0.0001475921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003555001,"about_ca_system_score_gemma":0.0006297556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001194438,"about_ca_topic_score_gemma":0.001734711,"domain_scores_codex":[0.9995416,0.0001423509,0.00004272786,0.00007904611,0.0001368609,0.00005732138],"domain_scores_gemma":[0.9996243,0.000149763,0.00007253171,0.00005158812,0.00007814045,0.00002366108],"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":[0.0008116438,0.0001548803,0.001859908,0.0007750205,0.0002962553,0.001277646,0.0007600201,0.4447508,0.08770941,0.05761219,0.007931549,0.3960606],"study_design_scores_gemma":[0.00007725375,0.0004499509,0.0005962324,0.00004207097,0.0001071129,0.0007692894,0.0002027596,0.9496541,0.02286664,0.01150035,0.01366961,0.00006469922],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03362145,0.00182054,0.9609972,0.0002657881,0.0001432687,0.0001668912,0.00008679649,0.0005945226,0.0023035],"genre_scores_gemma":[0.8004926,0.002008974,0.191668,0.0001835609,0.00007641136,0.0003889696,0.0002615778,0.00006491142,0.004854871],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001275974,"threshold_uncertainty_score":0.003196836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02047490358907133,"score_gpt":0.2508760028769197,"score_spread":0.2304010992878484,"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."}}