{"id":"W2071314084","doi":"10.1177/0037549705056220","title":"Power-Efficient Data Propagation Protocols for Wireless Sensor Networks","year":2005,"lang":"en","type":"article","venue":"SIMULATION","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Wireless sensor network; Protocol (science); Energy consumption; Distributed computing; Probabilistic logic; Efficient energy use; Computer network; Communications protocol; Fault tolerance; Cluster analysis; Hierarchy; Wireless; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009996265,0.0007638901,0.0004057279,0.0006663949,0.000439542,0.0005462783,0.0009688212,0.0006161274,0.001194293],"category_scores_gemma":[0.004339971,0.0003781053,0.0004446371,0.0009380092,0.0006374728,0.001336263,0.0007744624,0.0008806285,0.000273977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005098549,"about_ca_system_score_gemma":0.0006193783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001221987,"about_ca_topic_score_gemma":0.001602347,"domain_scores_codex":[0.9993677,0.0001919755,0.00004099296,0.00004210005,0.000323787,0.00003354934],"domain_scores_gemma":[0.9989485,0.0006086619,0.0001050061,0.0001438908,0.0001714892,0.00002247517],"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":[0.00006010775,0.00008961838,0.0004278068,0.0002066972,0.00005663983,0.00007334731,0.0001215077,0.879599,0.007176027,0.0622299,0.002333369,0.04762597],"study_design_scores_gemma":[0.00003863166,0.00007841977,0.0001050823,0.00002218612,0.00001862597,0.00005004355,0.00001656511,0.9682499,0.003318644,0.021719,0.006371143,0.00001186416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01970632,0.001171548,0.9744581,0.0003354774,0.0001399751,0.0002139752,0.00007625476,0.000297476,0.003600894],"genre_scores_gemma":[0.4841447,0.004178737,0.5039167,0.0002425089,0.00009805967,0.001083924,0.000349464,0.0001025951,0.005883398],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001221987,"threshold_uncertainty_score":0.005286634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0413010538275947,"score_gpt":0.3193729196601571,"score_spread":0.2780718658325624,"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."}}