{"id":"W2063603331","doi":"10.1145/2810362.2810365","title":"VARSA","year":2015,"lang":"en","type":"article","venue":"","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Wireless sensor network; Energy consumption; Computer science; Sleep mode; Real-time computing; Efficient energy use; RADIUS; Energy (signal processing); Tracking (education); Detector; Sensor node; Key distribution in wireless sensor networks; Wireless; Power consumption; Computer network; Engineering; Wireless network; Electrical engineering; Telecommunications; Power (physics); 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000945606,0.001170467,0.0007757705,0.001408219,0.001045522,0.003179925,0.003035632,0.001602605,0.1164906],"category_scores_gemma":[0.003517357,0.0005493292,0.001016926,0.00134765,0.0005097774,0.002793514,0.002647839,0.001442845,0.09023424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006936613,"about_ca_system_score_gemma":0.001421144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001650556,"about_ca_topic_score_gemma":0.001811137,"domain_scores_codex":[0.9987287,0.0002022455,0.00009611055,0.0003504252,0.0004550872,0.0001674947],"domain_scores_gemma":[0.9982548,0.0002863799,0.0001134267,0.0005435323,0.000648218,0.0001536869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008021782,0.0002996578,0.002494212,0.0008689619,0.0001139005,0.0004173275,0.0002650465,0.02157088,0.01424734,0.06494172,0.2435184,0.6504604],"study_design_scores_gemma":[0.0001231571,0.0002150785,0.001003271,0.0001595967,0.00005218881,0.0008337272,0.0001486463,0.04900235,0.01031664,0.02712039,0.9109386,0.00008626385],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.01958647,0.003819683,0.5214156,0.002602347,0.003741428,0.000708113,0.008419518,0.07440073,0.3653062],"genre_scores_gemma":[0.2398319,0.003936749,0.3012337,0.003029464,0.0009278096,0.0009368137,0.03464812,0.009623039,0.4058324],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.8835093,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03209315824709062,"score_gpt":0.2264392400715502,"score_spread":0.1943460818244596,"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."}}