{"id":"W2807060718","doi":"10.1016/j.future.2018.05.076","title":"Energy and connectivity aware resource optimization of nodes traffic distribution in smart home networks","year":2018,"lang":"en","type":"article","venue":"Future Generation Computer Systems","topic":"Energy Efficient Wireless Sensor Networks","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Home automation; Wireless sensor network; Energy consumption; Computer network; Efficient energy use; Constraint (computer-aided design); Distributed computing; Telecommunications; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004657089,0.0003572757,0.0005107633,0.0003751579,0.0003025606,0.0005367591,0.0006028119,0.00034216,0.000980345],"category_scores_gemma":[0.001395082,0.0002296288,0.0001620395,0.0005196369,0.000317862,0.0007820842,0.0003712897,0.000245633,0.00008587298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007784449,"about_ca_system_score_gemma":0.0003744737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002213219,"about_ca_topic_score_gemma":0.003817768,"domain_scores_codex":[0.9998264,0.00006065929,0.000005503403,0.00003034566,0.00003254093,0.00004460842],"domain_scores_gemma":[0.9996013,0.0002522063,0.00004217082,0.00001889964,0.00006307557,0.00002241756],"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":[0.0001053742,0.00005049344,0.0007951771,0.00002444581,0.00001771962,0.00003696974,0.00002958419,0.9675175,0.003038124,0.006658546,0.0006302907,0.02109575],"study_design_scores_gemma":[0.000001559762,0.00001121734,0.000179953,9.481733e-7,0.000003812821,0.0000073354,0.00001135403,0.9978682,0.0003351733,0.00150572,0.00007329733,0.000001399996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4429044,0.001039139,0.5482231,0.0005881638,0.00008179616,0.00004984074,0.0001234725,0.0002293942,0.006760676],"genre_scores_gemma":[0.9941002,0.0001227524,0.004730672,0.00001776929,0.00001431819,0.000009053977,0.00002031125,0.00001466762,0.0009701525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002213219,"threshold_uncertainty_score":0.005648077,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008378490089296973,"score_gpt":0.1936673701487114,"score_spread":0.1852888800594144,"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."}}