{"id":"W4407782497","doi":"10.1109/jiot.2025.3544224","title":"Enhancing Multilabel ECG Classification via Task-Guided Lead Correlations in Internet of Medical Things","year":2025,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"ECG Monitoring and Analysis","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Hamilton Health Sciences","funders":"National Natural Science Foundation of China","keywords":"Computer science; Task (project management); The Internet; Multi-label classification; Internet of Things; Lead (geology); Artificial intelligence; Machine learning; Data mining; Pattern recognition (psychology); Computer security; World Wide Web","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":[0.001657221,0.0001760313,0.0005727242,0.0007628212,0.00003535029,0.00003724866,0.000417281,0.0002630587,0.0001372663],"category_scores_gemma":[0.001135365,0.0001533053,0.0002625485,0.0004185166,0.0001295511,0.0003145756,0.00007056761,0.001190306,0.00001319057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00022467,"about_ca_system_score_gemma":0.0002220976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001329221,"about_ca_topic_score_gemma":0.00003727864,"domain_scores_codex":[0.997249,0.0001084179,0.001372896,0.0002396049,0.0007945253,0.0002355275],"domain_scores_gemma":[0.9983145,0.0002481122,0.0006753995,0.0002333485,0.0003880852,0.0001405747],"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":[0.0005853471,0.00162417,0.301408,0.0008856347,0.00160398,0.0002265025,0.0239976,0.0001477267,0.5584506,0.0006940605,0.01686919,0.09350716],"study_design_scores_gemma":[0.003449127,0.0003010473,0.01559872,0.01142852,0.0005384719,0.0004263269,0.001405156,0.7152471,0.2499509,0.0006779113,0.0007087897,0.0002678696],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7710478,0.0003300603,0.2231617,0.002590367,0.001270243,0.0001038829,6.327448e-7,0.00003031625,0.001465043],"genre_scores_gemma":[0.9891571,0.0001085956,0.005931185,0.0003579072,0.0001511932,0.000003911666,0.000005380545,0.00001680523,0.004267958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7150994,"threshold_uncertainty_score":0.6251608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02971184002147064,"score_gpt":0.3371504497416563,"score_spread":0.3074386097201856,"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."}}