Implementing Ammonia Measurement in Clinical Practice: Time to Forge Ahead
Bibliographic record
Abstract
The History of Ammonia in Hepatic EncephalopathyEven with the recent advancements for the treatment of hepatic encephalopathy (HE) over the last decade, HE still remains one of the most frequent and debilitating complications of cirrhosis.For several decades, it has been clearly established that the dysfunction of the cirrhotic liver to metabolise and detoxify ammonia leads to a substantial risk for hyperammonemia.Consequently, an influx of blood borne ammonia across the blood-brain barrier becomes neurotoxic, leading to deleterious effects on the brain [2].For this, hyperammonemia has, for close to a century, been declared as the primary factor in the pathophysiology of HE [3,4].Since then, ammonia has remained a cornerstone of mechanistic understanding, even though its role in diagnosis, severity and prognosis has frequently been debated and the usefulness of measuring plasma ammonia in clinical practice is often questioned.
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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 | 0.099 | 0.222 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.024 | 0.046 |
| Open science | 0.011 | 0.021 |
| Research integrity | 0.028 | 0.042 |
| Insufficient payload (model declined to judge) | 0.019 | 0.020 |
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".