A public health perspective on mitigating the global burden of chronic liver disease
Bibliographic record
Abstract
Chronic liver disease is a significant global health problem. Epidemiological trends do not show improvement in chronic liver disease incidence but rather a shift in etiologies, with steatotic liver disease (SLD) from metabolic dysfunction and alcohol becoming increasingly important causes. Consequently, there is a pressing need to develop a comprehensive public health approach for SLD. To that end, we propose a public health framework for preventing and controlling SLD. The framework is anchored on evidence linking physical inactivity, unhealthy dietary patterns, alcohol use, and obesity with both incidence and progression of SLD. Guided by the framework, we review examples of federal/state-level, community-level, and individual-level interventions with the potential to address these determinants of SLD. Ultimately, mitigating SLD's burden requires primary risk factor reduction at multiple socioecological levels, by scaling up the World Health Organization's "best buys," in addition to developing and implementing SLD-specific control interventions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".