{"id":"W2085512316","doi":"10.1016/j.jneumeth.2010.08.035","title":"Spike detection in human muscle sympathetic nerve activity using a matched wavelet approach","year":2010,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Microneurography; Wavelet; SIGNAL (programming language); Wavelet transform; Pattern recognition (psychology); Artificial intelligence; Computer science; Thresholding; Mathematics; Speech recognition; Medicine; Blood pressure; Heart rate; Baroreflex; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003105596,0.0002558234,0.0002492663,0.0003600368,0.0001385967,0.0003343328,0.0002319886,0.0004693511,0.0008469183],"category_scores_gemma":[0.001073224,0.0001480933,0.0003764649,0.000403698,0.0001508842,0.000428824,0.0003723422,0.0002894657,0.0002482322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007985952,"about_ca_system_score_gemma":0.0002114337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003254265,"about_ca_topic_score_gemma":0.0003876947,"domain_scores_codex":[0.999893,0.00002782603,0.000006898088,0.00001976568,0.00004087304,0.0000116717],"domain_scores_gemma":[0.9998111,0.0001136887,0.00001356598,0.0000151149,0.00003366771,0.0000128964],"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":[0.001342747,0.0002265461,0.00545587,0.0003098958,0.0001303219,0.000415141,0.0002019979,0.03927612,0.3916038,0.005358982,0.0007288913,0.5549496],"study_design_scores_gemma":[0.00005211453,0.0003093678,0.01242731,0.00002099067,0.00008257831,0.0006710046,0.00006344204,0.9309623,0.05132741,0.003089491,0.0009687101,0.00002531403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2301084,0.0003918336,0.7679237,0.0000941506,0.00005849524,0.00004419358,0.0001042669,0.0001622022,0.001112908],"genre_scores_gemma":[0.821174,0.0004717564,0.1762342,0.00005185721,0.00006335804,0.00005061659,0.0001650529,0.00004360323,0.001745624],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0008469183,"threshold_uncertainty_score":0.002833247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05476749761493915,"score_gpt":0.346819275489535,"score_spread":0.2920517778745958,"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."}}