Alanine Aminotransferase as an Independent Predictor of Incident Nonalcoholic Fatty Liver Disease
Bibliographic record
Abstract
We read with interest the recent article by Chang et al. (1) reporting that higher serum alanine aminotransferase (ALT) concentrations, within the reference interval, independently predicted the incidence of nonalcoholic fatty liver disease (NAFLD) during a mean follow-up of 2.5 years in a large cohort of apparently healthy Korean men. Several prospective studies have previously shown that increased ALT concentrations, even within the reference interval, also predict the future development of type 2 diabetes (2) and cardiovascular events (3) independently of other known risk factors. In all of these studies, however, increased ALT concentrations have been used as a surrogate marker of NAFLD. Indeed, increased liver enzymes are usually thought to be a consequence (and not a cause) of liver injury in …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".