{"id":"W1892839219","doi":"10.1002/cem.2533","title":"Statistical properties of signal entropy for use in detecting changes in time series data","year":2013,"lang":"en","type":"article","venue":"Journal of Chemometrics","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Entropy (arrow of time); Differential entropy; Time series; Sample entropy; Maximum entropy spectral estimation; White noise; Transfer entropy; Change detection; Series (stratigraphy); System identification; Algorithm; Data mining; Principle of maximum entropy; Artificial intelligence; Mathematics; Statistics; Machine learning; Measure (data warehouse)","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":[0.003967441,0.0007289783,0.0008043783,0.003535658,0.0004304463,0.001431689,0.0005898842,0.0008557466,0.001483096],"category_scores_gemma":[0.02506652,0.000275666,0.0008361791,0.002969345,0.001417825,0.002426974,0.001103277,0.001493617,0.0004319353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005279002,"about_ca_system_score_gemma":0.0006052404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007482697,"about_ca_topic_score_gemma":0.0004835999,"domain_scores_codex":[0.9985416,0.0004762403,0.0001539726,0.0002167694,0.0005454043,0.00006599785],"domain_scores_gemma":[0.981253,0.01443146,0.001556526,0.001655109,0.0008706739,0.0002332873],"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":[0.0005629219,0.0004145221,0.03247514,0.0007986508,0.0003924705,0.00142991,0.001006082,0.304443,0.08124152,0.1496238,0.003719894,0.423892],"study_design_scores_gemma":[0.00001509698,0.0002115809,0.01889937,0.00006562483,0.00005142828,0.0007366457,0.00008703501,0.9062942,0.01277853,0.05795516,0.002811203,0.00009424649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05924164,0.0008469516,0.935465,0.000278009,0.0001096541,0.00009488171,0.0005307196,0.001019671,0.002413629],"genre_scores_gemma":[0.7562692,0.001002643,0.2397661,0.0001537768,0.0003485905,0.0003333412,0.0009656979,0.0002707325,0.0008897835],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003967441,"threshold_uncertainty_score":0.02098203,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04068541875529027,"score_gpt":0.2369569219565983,"score_spread":0.1962715032013081,"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."}}