<i>HFE</i>-Associated Hereditary Haemochromatosis
Bibliographic record
Abstract
Hereditary hemochromatosis is a common inherited disorder of the iron metabolism. Screening studies indicate that it has a prevalence of one in 200 to 400, depending on the population studied, and a carrier rate of about one in seven to one in 10. Feder et al identified the hereditary hemochromatosis gene (HFE) in 1996 and two candidate mutations; the C282Y mutation has been shown to be responsible for the majority of the hereditary hemochromatosis cases worldwide. The gene discovery has led to rapid advances in the field of iron metabolism. Although the basic defect is still not fully understood, much is known about the sequence of events leading to iron overload. Hereditary hemochromatosis is a major candidate for population screening and meets the screening criteria of the World Health Organization, and Wilson and Jungner. It is one of the most prevalent genetic diseases in white populations, and, importantly, early diagnosis and simple effective treatment allow normal life expectancy. The discovery of the HFE gene and the frequency of the single C282Y mutation as a cause of most cases of hereditary hemochromatosis allow the possibility of widespread genetic testing. However, the logistics, and the psychological and social consequence of this, coupled with incomplete expression of the genotype, necessitate further studies before population screening can be justified.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".