{"id":"W1568291574","doi":"10.1109/ihtc.2014.7147524","title":"Accurate ECG R-peak detection for telemedicine","year":2014,"lang":"en","type":"article","venue":"","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Telemedicine; Computer science; Medical services; Medical emergency; Electrocardiography; Artificial intelligence; Medicine; Cardiology; Health care","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":[0.000608766,0.0006350756,0.0006622804,0.0009922221,0.000249779,0.0010839,0.0009178866,0.001303737,0.0103375],"category_scores_gemma":[0.002309235,0.0003447426,0.0002528765,0.0008052245,0.0002926591,0.001026366,0.000601856,0.000725053,0.006846841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002842205,"about_ca_system_score_gemma":0.0002709035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004533797,"about_ca_topic_score_gemma":0.0006512642,"domain_scores_codex":[0.9992349,0.0002032642,0.00004250086,0.0001781983,0.0002966078,0.00004451254],"domain_scores_gemma":[0.9991685,0.0002904465,0.00006744547,0.0001669962,0.000266212,0.00004039015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005836513,0.0001356034,0.002433966,0.0004386714,0.00003574135,0.0003163541,0.00007690891,0.004409917,0.2639931,0.005031698,0.01505935,0.7074852],"study_design_scores_gemma":[0.0002962987,0.001648755,0.02355517,0.0005938514,0.0002293308,0.006613362,0.0002462067,0.3437308,0.4610865,0.01764189,0.1441062,0.0002515933],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02059217,0.007911095,0.9507332,0.001060162,0.0005744502,0.0001589165,0.0008473819,0.00687595,0.01124665],"genre_scores_gemma":[0.438446,0.004574134,0.5415182,0.0009249852,0.0007738357,0.0001217914,0.000939794,0.0004346904,0.01226674],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0103375,"threshold_uncertainty_score":0.03458238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01774911117783474,"score_gpt":0.302805146376125,"score_spread":0.2850560351982903,"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."}}