Melanin quantification by in vitro and in vivo analysis of near‐infrared fluorescence
Bibliographic record
Abstract
Summary Objective measurements of melanin can provide important information for differentiating melanoma from benign pigmented lesions and in assessing pigmentary diseases. Herein, we evaluate near‐infrared (NIR) fluorescence as a possible tool to quantify melanin. Various concentrations of in vitro Sepia melanin in tissue phantoms were measured with NIR fluorescence and diffuse reflectance spectroscopy. Similar optic measurements were conducted in vivo on 161 normal human skin sites. Diffuse reflectance spectroscopy was used to quantify the melanin content via Stamatas–Kollias algorithm. At physiologic concentrations, increasing in vitro melanin concentrations demonstrated higher fluorescence that was linearly correlated ( R 2 = 0.99, p < .001). At higher concentrations, the fluorescence signal plateaued. A linear relationship was also observed with melanin content in human skin ( R 2 = 0.59, p < .001). Comparing the fluorescence and reflectance signals with in vitro and in vivo samples, the estimated melanin concentration in human skin ranged between 0 and 1.25 mg/ml, consistent with previous quantitative studies involving invasive methods.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".