{"id":"W2120185982","doi":"10.1109/hicss.2001.927199","title":"Internal nodes based broadcasting in wireless networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada); University of Ottawa","funders":"","keywords":"Broadcasting (networking); Computer science; Computer network; Node (physics); Overhead (engineering); Wireless network; Reduction (mathematics); Wireless; Distributed computing; Telecommunications; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003319905,0.0001820792,0.0001863051,0.000177263,0.00006762423,0.0001750446,0.0009954212,0.00009750101,0.00004469844],"category_scores_gemma":[0.00001753936,0.0001704478,0.00006481523,0.0005994554,0.0000412204,0.0003639895,0.0002363985,0.0002957443,0.00003559918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009872144,"about_ca_system_score_gemma":0.00003187319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001170636,"about_ca_topic_score_gemma":0.0003010668,"domain_scores_codex":[0.998308,0.0000861677,0.0003469341,0.0004615855,0.0002600239,0.0005372968],"domain_scores_gemma":[0.9990638,0.0002312858,0.00008367702,0.0004686307,0.00004678569,0.0001057885],"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":[0.000004500396,0.00006611682,0.004568977,0.000001957826,0.000002570892,0.00002021223,0.00004263416,0.8826703,0.0001105912,0.0104002,0.0001947102,0.1019172],"study_design_scores_gemma":[0.0004108528,0.00001636566,0.002045525,0.00006922914,0.000001004768,0.000009546014,0.000006508123,0.9953928,0.001180214,0.00001322524,0.0006461495,0.0002085528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1147543,0.00006856382,0.8726013,0.0006063914,0.0002778187,0.00005818785,1.074712e-7,0.0002768123,0.01135653],"genre_scores_gemma":[0.9111576,0.000005845292,0.08713764,0.001069012,0.0002282567,0.0000066746,0.000001342559,0.0000145995,0.0003790154],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7964033,"threshold_uncertainty_score":0.6950659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008882276748573533,"score_gpt":0.2183248978609699,"score_spread":0.2094426211123963,"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."}}