{"id":"W4236059287","doi":"10.21203/rs.3.rs-17367/v1","title":"Multichannel ECG Recording from Waist using Textile Sensors","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Toronto Rehabilitation Institute; University of Waterloo; University of Toronto","funders":"","keywords":"Waist; Textile; Computer science; Acoustics; Environmental science; Materials science; Medicine; Internal medicine; Physics; Composite material","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":[0.0001593486,0.0003648007,0.0002915268,0.0003175118,0.0001403991,0.0004028781,0.0002042649,0.0004940074,0.004975764],"category_scores_gemma":[0.0005317549,0.0001315724,0.0001850192,0.0004107716,0.00009135442,0.0003281911,0.0002417043,0.0001811643,0.0008442042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006035018,"about_ca_system_score_gemma":0.00007753514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003567747,"about_ca_topic_score_gemma":0.0005528537,"domain_scores_codex":[0.9997711,0.00003809518,0.00001206084,0.00007412801,0.00008545623,0.00001926744],"domain_scores_gemma":[0.999739,0.0001033836,0.00001927342,0.0000654464,0.00005660577,0.00001623706],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007791469,0.00009547649,0.004494336,0.0002596285,0.00007109651,0.0004334654,0.0001797061,0.001484206,0.828926,0.0005898193,0.00206469,0.1606224],"study_design_scores_gemma":[0.0001480102,0.001681681,0.1705849,0.00007655605,0.0003059078,0.005792656,0.0002426607,0.1064484,0.6962278,0.002057991,0.01634898,0.00008440592],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5108853,0.001038951,0.4691769,0.0002922682,0.0003423003,0.0001173265,0.00232631,0.00222687,0.01359374],"genre_scores_gemma":[0.8950887,0.0005763959,0.09251176,0.0001028843,0.0002365533,0.000046076,0.0007601869,0.0001340244,0.01054343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004975764,"threshold_uncertainty_score":0.01664561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2434085923173799,"score_gpt":0.4697104447949548,"score_spread":0.2263018524775749,"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."}}