{"id":"W4416612861","doi":"10.1186/s12859-025-06276-0","title":"CLEP-GAN: an innovative approach to subject-independent ECG reconstruction from PPG signals","year":2025,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Fields Institute for Research in Mathematical Sciences; Canada Research Chairs","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Normal Sinus Rhythm; Sinus rhythm; RR interval; Pattern recognition (psychology); Atrial fibrillation; Electrocardiography","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":[0.001076189,0.0009900309,0.0006527543,0.0004487331,0.000157417,0.0005751904,0.001496619,0.001001179,0.002258649],"category_scores_gemma":[0.002714774,0.0004081474,0.000885867,0.0003784472,0.0004973448,0.0005781685,0.001247442,0.001979156,0.0008806164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003692521,"about_ca_system_score_gemma":0.0005501193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001401343,"about_ca_topic_score_gemma":0.002647645,"domain_scores_codex":[0.9995733,0.000167511,0.00001725523,0.0001078125,0.0001033989,0.00003068558],"domain_scores_gemma":[0.9992163,0.0004484832,0.0000543875,0.0001388218,0.00009719034,0.00004468315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002498434,0.0001402499,0.002190997,0.0002147258,0.0001965349,0.0004217537,0.000101869,0.7047236,0.01744376,0.009116987,0.01602331,0.2491764],"study_design_scores_gemma":[0.000008636785,0.00002880546,0.000239723,0.0000122383,0.000008733535,0.0001329953,0.000004851496,0.992373,0.002123865,0.003260222,0.001797948,0.000008815844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007449926,0.0004911501,0.9878996,0.0003000537,0.00007352123,0.00006336433,0.0003191692,0.00159081,0.001812402],"genre_scores_gemma":[0.4286495,0.001070659,0.5552327,0.001509365,0.0003217649,0.000376333,0.003513106,0.0009337777,0.008392914],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002258649,"threshold_uncertainty_score":0.007555962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0284596599073604,"score_gpt":0.2914696153237213,"score_spread":0.2630099554163609,"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."}}