Seasonal variability in the activity of common chronic liver diseases
Bibliographic record
Abstract
BACKGROUND: Seasonal variations in flu-like illnesses and vaccinations, vitamin D levels, alcohol intake, and sedentary lifestyles raise the possibility that seasonal variations exist in the severity of immune-mediated, alcohol, and obesity- or dyslipidemia-related chronic liver diseases, respectively. METHODS: We documented months-seasons in which biochemical evidence of disease activity is greatest in adult patients with common liver disorders. Months-seasons associated with peak liver enzyme levels in patients with largely immune-mediated disorders (autoimmune hepatitis, primary biliary cholangitis [PBC], and primary sclerosing cholangitis), alcoholic liver disease, and non-alcoholic fatty liver disease were documented from a hospital-based, liver diseases outpatient clinic database. RESULTS: < .005), no significant associations were found between months-seasons and peak liver enzyme activities in any of these liver disorders. CONCLUSIONS: These findings suggest that seasonal illnesses or immunizations and vitamin D depletion, alcohol intake, and sedentary lifestyle do not significantly exacerbate common underlying immune-mediated, alcohol, or metabolic liver disorders, respectively.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".