U Wave Variability in the Surface ECG
Bibliographic record
Abstract
A 72-year-old man with heart failure, left ventricular dysfunction (ejection fraction 20%), prior ischemic stroke, COPD, and exacerbation of chronic renal failure was admitted in our unit. Serum potassium was 6.1 mmol/L, calcium concentration was at the lower normal range 2.15 mmol/L, and NT-pro-BNP was 28,900 pg/mL. The surface 12-lead electrocardiogram (ECG) showed sinus rhythm at 60 bpm, PR interval 160 ms, QRS duration 115 ms, QT interval 460 ms, and left ventricular hypertrophy criteria. Negative T waves in leads I, II, aVL, and V4 -V6 were also seen. In leads V4 -V6 , negative U waves were observed in concordance with negative T waves. In all precordial leads, beat-to-beat U-wave polarity variability was observed as a polarity variation from negative to positive with associated and stable negative T waves, in a beat-to-beat alternate morphology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".