{"id":"W2999010100","doi":"10.3390/s20020567","title":"Performance Analysis of Distributed Estimation for Data Fusion Using a Statistical Approach in Smart Grid Noisy Wireless Sensor Networks","year":2020,"lang":"en","type":"article","venue":"Sensors","topic":"Distributed Sensor Networks and Detection Algorithms","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Wireless sensor network; Smart grid; Real-time computing; Sensor fusion; Distributed computing; Wireless; Grid; Data aggregator; Data mining; Computer network; Engineering; Artificial intelligence; Telecommunications","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":[0.0003561205,0.0001900979,0.000477018,0.0001788734,0.0001131841,0.00008932513,0.0005819662,0.0001145372,0.000005183467],"category_scores_gemma":[0.0001035044,0.0001863139,0.00008472642,0.002609109,0.00006232363,0.0002815367,0.0002581567,0.0001853014,0.000001446593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005286552,"about_ca_system_score_gemma":0.00004007245,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007030387,"about_ca_topic_score_gemma":0.00001091391,"domain_scores_codex":[0.9980174,0.00010972,0.0005523817,0.0006549464,0.0003069869,0.0003585204],"domain_scores_gemma":[0.9986267,0.0002134076,0.0002260174,0.0006461043,0.0001345183,0.0001532608],"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":[0.00006735417,0.00006527199,0.001412117,0.00004051864,0.0001039464,0.000004723659,0.0001031035,0.9806036,0.00004877361,0.0002446827,0.0001735455,0.01713236],"study_design_scores_gemma":[0.0004357139,0.00007146176,0.004986756,0.00001573926,0.0001706447,0.000004578805,0.00005568823,0.9938601,0.00005630302,0.000008480006,0.000133365,0.0002012305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2352967,0.0000115915,0.7634462,0.00009294045,0.0001400009,0.0002417218,0.0006895327,0.00006752301,0.00001383049],"genre_scores_gemma":[0.798217,0.00001434944,0.199189,0.00005955987,0.00007875213,0.000005318401,0.00242257,0.00001149831,0.000001920867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5642571,"threshold_uncertainty_score":0.7597662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0445600269464031,"score_gpt":0.2735282659728782,"score_spread":0.2289682390264751,"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."}}