{"id":"W2082012113","doi":"10.1038/jes.2012.102","title":"Characterization of radiofrequency field emissions from smart meters","year":2012,"lang":"en","type":"article","venue":"Journal of Exposure Science & Environmental Epidemiology","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Tellabs (Canada); Nortel (Canada)","funders":"Electric Power Research Institute","keywords":"Smart meter; Spectrum analyzer; Environmental science; Duty cycle; Metre; Sample (material); Sampling (signal processing); Remote sensing; Field (mathematics); Electrical engineering; Telecommunications; Engineering; Voltage; Smart grid; Geography; Physics; Mathematics","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":[0.0001889412,0.000175073,0.0001682579,0.0005268772,0.0001465539,0.0002597718,0.0001935399,0.0003618194,0.001113437],"category_scores_gemma":[0.0005072965,0.0000849599,0.0001504793,0.0003015421,0.0001152214,0.0003354099,0.0001509531,0.0001318773,0.0002940788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008645034,"about_ca_system_score_gemma":0.00006424163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004029987,"about_ca_topic_score_gemma":0.0004697718,"domain_scores_codex":[0.9997784,0.00004192855,0.00001142902,0.00005201354,0.00008965834,0.00002653943],"domain_scores_gemma":[0.9996688,0.0001348163,0.00005580159,0.00003106857,0.00009699661,0.00001248514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001267514,0.0002212238,0.1696352,0.000180591,0.00008550209,0.0005561513,0.0004192261,0.005468488,0.7454171,0.0004153992,0.0007694947,0.07556411],"study_design_scores_gemma":[0.00004691467,0.001799895,0.5887883,0.00004298724,0.0001183787,0.002245155,0.0008291781,0.03683887,0.3635489,0.0005826947,0.00511957,0.00003923802],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882715,0.0001458609,0.009935033,0.00003360581,0.000013123,0.00002078776,0.0002902265,0.00007927704,0.001210487],"genre_scores_gemma":[0.9975241,0.00005683665,0.001372587,0.00002196958,0.000007322046,0.00001062976,0.0002003973,0.000007144421,0.0007989855],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001113437,"threshold_uncertainty_score":0.003724813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02350202258681372,"score_gpt":0.2638784942310381,"score_spread":0.2403764716442244,"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."}}