Association of HFE genotypes with hemochromatosis-related phenotypes in the All of Us research program
Bibliographic record
Abstract
Purpose: variation with HH-related phenotypes and assess the prevalence of testing and diagnosis of HH using All of Us data. Methods: genotypes, we examined the prevalence of HH diagnosis codes and related biochemical and clinical phenotypes. Results: = .0001). Of the 71 participants who were p.Cys282Tyr homozygotes with indication of liver disease, 32 (45.1%) did not have a serum transferrin-iron saturation measure, and 37 (52.1%) did not have diagnosis codes for HH. Conclusion: Limited serum transferrin-iron saturation measures or HH diagnosis codes among p.Cys282Tyr homozygotes, even those with liver disease, suggests potential undertesting and underdiagnosis of type 1 HH in clinical practice and a need for improved awareness, education, and testing around HH.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".