Initial screening transferrin saturation values, serum ferritin concentrations, and<i>HFE</i>genotypes in Native Americans and whites in the Hemochromatosis and Iron Overload Screening Study
Bibliographic record
Abstract
We compared initial screening transferrin saturation (TfSat) and serum ferritin (SF) phenotypes and HFE C282Y and H63D genotypes of 645 Native American and 43,453 white Hemochromatosis and Iron Overload Screening Study participants who did not report a previous diagnosis of hemochromatosis or iron overload. Elevated measurements were defined as TfSat >50% in men and >45% in women and SF >300 ng/ml in men and >200 ng/ml in women. Mean TfSat was 31% in Native American men and 32% in white men (p = 0.0337) and 25% in Native American women and 27% in white women (p < 0.0001). Mean SF was 153 microg/l in Native American and 151 microg/l in white men (p = 0.8256); mean SF was 55 microg/l in Native American women and 63 microg/l in white women (p = 0.0015). The C282Y allele frequency was 0.0340 in Native Americans and 0.0683 in whites (p < 0.0001). The H63D allele frequency was 0.1150 in Native Americans and 0.1532 in whites (p = 0.0001). We conclude that the screening TfSat and SF phenotypes of Native Americans are similar to those of whites. The allele frequencies of HFE C282Y and H63D are significantly lower in Native Americans than in whites.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".