{"id":"W2167641880","doi":"10.1109/glocom.2005.1578302","title":"LPT for data aggregation in wireless sensor networks","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Wireless sensor network; Data aggregator; Computer science; Sink (geography); Computer network; Distributed computing; Tree (set theory); Overlay; Routing protocol; Routing (electronic design automation)","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":[0.001971347,0.000692951,0.0008066615,0.0006767887,0.0007296917,0.001018984,0.001191684,0.000954567,0.001867004],"category_scores_gemma":[0.005469099,0.0002872274,0.0006766449,0.001714854,0.0007842126,0.001998428,0.001351034,0.001511318,0.001028399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006994905,"about_ca_system_score_gemma":0.0006924272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007711441,"about_ca_topic_score_gemma":0.0006873659,"domain_scores_codex":[0.9987872,0.0003861035,0.0001062666,0.000182402,0.0004835743,0.00005443912],"domain_scores_gemma":[0.9986839,0.0006956461,0.0001382297,0.0002410249,0.0002042591,0.00003688549],"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":[0.0002684454,0.00008216852,0.0008805309,0.0005882019,0.0001118556,0.0004030438,0.0003210368,0.2416948,0.01266261,0.1341098,0.01297505,0.5959026],"study_design_scores_gemma":[0.00002764483,0.0001293573,0.0001571871,0.00004798716,0.00002895367,0.0002843751,0.00003720519,0.9007922,0.004355861,0.07262405,0.02149689,0.00001815728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001566242,0.0009341028,0.995479,0.0002496812,0.0001416027,0.00005656472,0.00002363793,0.000421946,0.001127179],"genre_scores_gemma":[0.1600481,0.00287773,0.8302007,0.0005413102,0.00046607,0.0006209136,0.000263164,0.0002512034,0.004730728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001971347,"threshold_uncertainty_score":0.01042563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04590402469165972,"score_gpt":0.2974597009914756,"score_spread":0.2515556762998158,"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."}}