Association between quantitative measures of skin color & plasma 25‐hydroxyvitamin D (25OHD)
Bibliographic record
Abstract
Most vitamin D is obtained through UV synthesis in the skin. Dark‐skin ethnic groups have lower 25OHD concentrations than light skin groups; due to more skin melanin, which acts as a UV filter. Ethnicity is a proxy measure of skin color & within an ethnic group skin color varies greatly. It would be expected that the color of unexposed skin would be negatively associated with 25OHD. Conversely, as skin color darkens with sun exposure, a measure of tanning would be positively associated with 25OHD. Skin color can be quantified using reflectance colorimetry with higher numbers indicating darker skin. We aimed to determine the association between constitutive (upper inner‐arm) & sun‐induced (forearm) skin color & 25OHD in a group of Pacific Islanders (n=82) & Europeans (n=239) living in NZ (47°S) in summer. Mean (SD) serum 25OHD was 88 (31) nmol/L for Europeans and 75 (34) nmol/L for Pacific Islanders. Based on constitutive skin color measurements 36% of participants were very light, 45% light, 15% intermediate, 4% tanned, & 1% dark. Tanning at the forearm but not constitutive skin color was a significant predictor of 25OH D. Each 10 unit higher value at the forearm (less tanning) was associated with a ~4.9 nmol/L lower 25OHD (P<0.001). Tanning was a more important predictor of 25OHD than constitutive skin color in this population. Further study is needed in a population with a wider range of constitutive skin color.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".