{"id":"W4253217168","doi":"10.1109/iembs.2005.1615307","title":"A Wavelet Approach to Detecting Electrocautery Noise in the ECG","year":2005,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"","keywords":"Noise (video); Computer science; Wavelet; Software; SIGNAL (programming language); Wavelet transform; Artificial intelligence; Real-time computing; Pattern recognition (psychology)","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":[0.0003197654,0.00007027871,0.0001278479,0.0001112616,0.00004209715,0.00001839399,0.00007875553,0.00003160612,0.00001271163],"category_scores_gemma":[0.00006650103,0.00004163796,0.00005742209,0.0003897024,0.000005745123,0.00002763662,0.00001382484,0.0001714397,0.00004991165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000433609,"about_ca_system_score_gemma":0.00001544364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009426587,"about_ca_topic_score_gemma":0.00004153019,"domain_scores_codex":[0.9993422,0.00002716467,0.0001283456,0.000151332,0.0001476526,0.0002032802],"domain_scores_gemma":[0.9996725,0.00004158427,0.00001443761,0.0002028505,0.00001745645,0.00005119772],"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":[0.0001558543,0.001212682,0.07837342,0.0001006251,0.0001926487,0.00005046466,0.008519383,0.0006790182,0.06785097,0.0002640933,0.004990171,0.8376107],"study_design_scores_gemma":[0.00677879,0.001645737,0.1822731,0.0004364258,0.0009124913,0.0009287851,0.02185202,0.4864054,0.2101069,0.0002163544,0.08674509,0.001698934],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9448798,0.0000563564,0.009611401,0.003728832,0.00001734484,0.0001401522,1.231872e-7,0.00005557576,0.04151044],"genre_scores_gemma":[0.9737912,0.000005035088,0.02172735,0.001788371,0.0004298287,0.00002135189,0.00000132871,0.000007623048,0.002227922],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8359118,"threshold_uncertainty_score":0.1697947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01927056894368762,"score_gpt":0.2702862980953383,"score_spread":0.2510157291516507,"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."}}