{"id":"W2133451802","doi":"10.1016/j.comcom.2004.12.034","title":"Serialized optimal relay schedules in two-tiered wireless sensor networks","year":2005,"lang":"en","type":"article","venue":"Computer Communications","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Relay; Computer science; Wireless sensor network; Computer network; Provisioning; Node (physics); Overhead (engineering); Base station; Wireless; Cluster (spacecraft); Topology (electrical circuits); Process (computing); Distributed computing; Telecommunications; Electrical engineering; 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":[0.003056125,0.001138298,0.002257338,0.0007825572,0.0007251339,0.001495561,0.002524614,0.001035551,0.002758122],"category_scores_gemma":[0.007792274,0.001111916,0.0005075454,0.001472083,0.001035853,0.002176223,0.001389799,0.00096617,0.0004300794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00166953,"about_ca_system_score_gemma":0.002373753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003933031,"about_ca_topic_score_gemma":0.007428154,"domain_scores_codex":[0.9982102,0.0007610638,0.0001274212,0.0002748828,0.0003316681,0.000294745],"domain_scores_gemma":[0.9945771,0.003145859,0.0006137999,0.0006614514,0.0007365546,0.0002652999],"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":[0.000479182,0.00007609672,0.0002867017,0.00008792213,0.00003193975,0.00007269964,0.00007845353,0.9658154,0.002479729,0.01113023,0.001410967,0.01805071],"study_design_scores_gemma":[0.00004259847,0.00009687746,0.0001249156,0.000004188517,0.00001236009,0.00002905769,0.00001857418,0.991758,0.000580343,0.007099234,0.0002246211,0.000009163758],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1203175,0.0007015295,0.8729874,0.0004668781,0.0001544603,0.0002533232,0.000406479,0.000710218,0.004002261],"genre_scores_gemma":[0.87019,0.0003918514,0.1243671,0.000137636,0.00008198692,0.0002165038,0.0003073116,0.0001277717,0.004179922],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003933031,"threshold_uncertainty_score":0.01616251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081356204800513,"score_gpt":0.279097683919875,"score_spread":0.2582841218718699,"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."}}