{"id":"W4408113412","doi":"10.1063/5.0245129","title":"Median method for robust and accurate power spectral density estimation of stochastic oscillators","year":2025,"lang":"en","type":"article","venue":"Review of Scientific Instruments","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Spectral density; Smoothing; Standard deviation; Noise (video); Context (archaeology); Mathematics; Spectral density estimation; Stochastic resonance; Noise spectral density; Spectral leakage; Noise reduction; Statistics; Algorithm; Physics; Computer science; Mathematical analysis; Acoustics; Noise figure; Telecommunications; Bandwidth (computing)","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":[0.0006826788,0.0001062319,0.0003004051,0.0001555893,0.00006675438,0.00001627361,0.0001275344,0.00004429479,0.000007311862],"category_scores_gemma":[0.0001856244,0.00009609313,0.00004998097,0.0003614081,0.00008036092,0.0001067973,0.00003680829,0.0000618881,5.736663e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007928835,"about_ca_system_score_gemma":0.00004218693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008251312,"about_ca_topic_score_gemma":0.000001591521,"domain_scores_codex":[0.9990582,0.00002312892,0.0004113332,0.0001736222,0.0001703105,0.0001634438],"domain_scores_gemma":[0.9994648,0.00006085653,0.0001085396,0.0002141818,0.0001044378,0.00004723765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001250354,0.00001487339,0.0004129694,0.03393735,0.00006641791,2.226588e-7,0.0001520003,0.0009329317,0.002251372,0.001936736,0.001308176,0.9589744],"study_design_scores_gemma":[0.001201976,0.0002007931,0.03442711,0.05007733,0.0003790697,0.00001764503,0.00007804432,0.7231969,0.1745604,0.01407657,0.001043614,0.0007405518],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9285786,0.002257352,0.06525856,0.00008171954,0.002388157,0.001161873,0.000039205,0.0001037135,0.0001307957],"genre_scores_gemma":[0.8644347,0.0004492104,0.1350423,0.00001281592,0.000008436496,0.00001901554,0.000008533969,0.000007481232,0.00001744696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9582339,"threshold_uncertainty_score":0.3918564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02329486184747048,"score_gpt":0.3347074231045279,"score_spread":0.3114125612570575,"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."}}