{"id":"W4402168464","doi":"10.3390/bioengineering11090883","title":"Automatic Classification of Anomalous ECG Heartbeats from Samples Acquired by Compressed Sensing","year":2024,"lang":"en","type":"article","venue":"Bioengineering","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Pattern recognition (psychology); Discrete cosine transform; Artificial intelligence; Computer science; Feature extraction; Compressed sensing; Feature (linguistics); Image (mathematics)","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":[0.00006442713,0.0001070789,0.000237253,0.0001224114,0.00002342105,0.00003022713,0.00003658312,0.00005669329,0.00002464769],"category_scores_gemma":[0.00003431155,0.00009963239,0.00008445809,0.000223296,0.00001946225,0.00004552511,0.0000126993,0.00005782626,0.00001290399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004629956,"about_ca_system_score_gemma":0.00002077068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000161981,"about_ca_topic_score_gemma":0.000001031378,"domain_scores_codex":[0.99931,0.00001098503,0.0002221659,0.0001787298,0.0001457803,0.0001323772],"domain_scores_gemma":[0.99958,0.00009726742,0.00002723008,0.0002021783,0.0000288256,0.00006450919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003885901,0.00001919519,0.002657359,0.0002812901,0.0001602235,0.00001308729,0.0001524716,0.0001354455,0.9633757,0.000007392709,0.0004593942,0.0327345],"study_design_scores_gemma":[0.0001601821,0.00002974507,0.01564051,0.0007121799,0.0001725709,0.000007360801,0.00009133666,0.8924974,0.08949266,0.000008264637,0.001085817,0.0001020264],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9594036,0.002967181,0.03662143,0.0002500649,0.0002515039,0.00007018132,0.00002801786,0.0003618849,0.00004609062],"genre_scores_gemma":[0.9850444,0.00003140348,0.01454605,0.00000746416,0.0001765819,0.000001846326,0.00008523415,0.00002522105,0.00008182072],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8923619,"threshold_uncertainty_score":0.4062891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02735071434063851,"score_gpt":0.2686906942223647,"score_spread":0.2413399798817262,"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."}}