X-ray fluorescence measurements of arsenic micro-distribution in human nail clippings using synchrotron radiation
Bibliographic record
Abstract
Arsenic (As) distribution in nail clippings from three healthy human subjects was investigated using the microbeam experimental setup of the hard x-ray micro-analysis (HXMA) beamline from the Canadian Light Source (CLS) synchrotron. A pair of toenail and fingernail clippings was collected from each of three subjects (one contributed two fingernail clippings). The fingernail and toenail clippings were embedded in polyester resin and cut in cross-sectional slices with an average thickness of 270 µm. Nine nail clipping cross sections were analyzed from the three subjects. The same method was used to produce five cross sections of nail phantom clippings with concentrations of As ranging from 0 to 20 µg g−1, in increments of 5 µg g−1. These samples were used to produce a calibration line for the As Kα peak. The energy of the x-ray beam was set at 13 keV for optimal excitation of As and the beam size was 28 × 10 µm2. Each sample was analyzed using a point-by-point scanning technique in a 45° beam-sample and 90° beam-detector geometry. The dwelling time was set at 30 s for the human nail clippings and 20 s for the nail phantom clippings, using a step size of 50 µm in both the horizontal and vertical directions for all samples. As concentration for each point was calculated based on the calibration line parameters and the fitted amplitude of the observed As Kα peak. As concentration maps were produced for each nail clipping cross section. The maps show that small regions (<0.1 mm2) with higher As concentrations (>1 µg g−1) are located predominantly in the ventral and dorsal layers of the nail. The results are in agreement with findings reported in a recent study and can be linked to nail histology and keratin structure.
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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 | 0.000 |
| 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".