Comparing Quantitative Measures of Erythema, Pigmentation and Skin Response using Reflectometry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We measured a number of pigmentation and skin response phenotypes in a sample of volunteers (n=397) living in State College, PA. The majority of this sample was composed of four groups based on stated ancestry: African-American, European-American, Hispanic and East Asian. Several measures of melanin concentration (L*, melanin index and adjusted melanin index) were estimated by diffuse reflectance spectroscopy and compared. The efficacy of these measures for assessing constitutive pigmentation and melanogenic dose-response was evaluated. Similarly, several measures of erythema (a*, erythema index and adjusted erythema index) were compared and evaluated in their efficacy in measuring erythema and erythemal dose-response. We show a high correspondence among all of the measures for the assessment of constitutive pigmentation and baseline erythema. However, our results demonstrate that evaluating melanogenic dose-response is highly dependent on the summary statistic used: while L* is a valid measure of constitutive pigmentation it is not an effective measure of melanogenic dose-response. Our results also confirm the use of a*, as it is shown to be highly correlated with the adjusted erythema index, a more advanced measure of erythema based on the apparent absorbance. Diffuse reflectance spectroscopy can be used to quantify the constitutive pigmentation, melanogenic dose-response at 7 d and erythemal dose-response at both 24 h and 7 d postexposure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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) | 0.000 | 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 it