Implementing genetic screening for the management of hepatic disease
Bibliographic record
Abstract
Liver cirrhosis is an advanced stage of liver fibrosis causing liver failure, and may progress to hepatocellular carcinoma (HCC). HCC remains as the second leading cause of cancer-related deaths worldwide and is one of few cancer types to show increasing incidence and mortality rates (1). HCC incidence has doubled in low-risk countries such as USA, Canada, Australia, and some European countries since the 1970s (2) and mortality rates have increased in these regions, especially in 45+ age groups (3). This may be attributed to intravenous drug use in this cohort associated with high HCV infection rates between 1960–1980 (4). Additionally, an increasing amount of HCC cases are non-viral (5). Thus, the rise in HCC deaths in Westernized countries may be attributed to increased obesity and diabetes prevalence, both well-established risk factors for non-alcoholic fatty liver disease (NAFLD), non-alcoholic hepatic steatosis (NASH), and progression to HCC. Regardless of original cause, 85–90% of HCC cases arise from underlying cirrhosis and non-cirrhotic cases show varying stages of fibrosis. Unfortunately, progression of hepatic fibrosis to cirrhosis is often asymptomatic and most diagnoses are not made until clinical signs arise indicating end-stage liver disease (ESLD) or advanced HCC (6). Thus, a relevant strategy of reducing liver disease-related deaths are to take preventative measures and improve disease management.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".