{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004118014,0.0002193272,0.0003257679,0.000147624,0.0001766001,0.0002264538,0.0003352536,0.0002228339,0.000001240035],"category_scores_gemma":[0.000004485296,0.0002146469,0.00004553366,0.0006805485,0.00007618001,0.0003180447,0.0001468594,0.0001052454,6.412649e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008219616,"about_ca_system_score_gemma":0.00003294548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005549986,"about_ca_topic_score_gemma":0.0001778803,"domain_scores_codex":[0.9979451,0.0004356302,0.0004874111,0.0005709233,0.0002749959,0.000285986],"domain_scores_gemma":[0.9988436,0.00008760208,0.000259682,0.0004763805,0.0002480664,0.00008466976],"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":[0.000007643231,0.00004488066,0.0002716741,0.00001380355,0.00001127479,0.000002798885,0.0001961299,0.9760232,0.000024752,0.007595519,0.006779642,0.009028714],"study_design_scores_gemma":[0.0003948084,0.0001211793,0.000558264,0.00006349776,0.000004370058,0.00002582706,0.00001893465,0.9918485,0.0001121798,7.172345e-7,0.006633685,0.0002179829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0484062,0.0007209494,0.9386851,0.0001616508,0.01172188,0.0001468445,0.000006286698,0.0001281639,0.00002296823],"genre_scores_gemma":[0.9727153,0.00004357574,0.009001176,0.00008770617,0.01789536,0.00001853295,0.0001983855,0.00001653725,0.00002346159],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9296839,"threshold_uncertainty_score":0.8753049,"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."}}