Simultaneous assessment of arsenic and selenium in human nail phantoms using a portable x-ray tube and a detector
Bibliographic record
Abstract
A novel approach to the measurement of arsenic and selenium in nail phantoms is demonstrated. Two-component nail phantoms of 0.7 mm and 1.5 mm thickness were made from a polyester resin-salt mixture and dosed with equal arsenic and selenium concentrations ranging from 0 to 30 microg g(-1). A backing was made to simulate the soft tissue and bone of the great toe. Characteristic x-rays for arsenic and selenium were recorded using a portable x-ray tube and a silicon PiN diode detector. The minimum instrumental detection limits for arsenic and selenium in 0.7 mm solitary nail samples were as follows: 0.510 +/- 0.018 microg g(-1) and 0.519 +/- 0.026 microg g(-1) respectively; for 1.5 mm solitary nail: 0.465 +/- 0.035 microg g(-1) and 0.561 +/- 0.062 microg g(-1); for 0.7 mm nail with backing: 1.522 +/- 0.038 microg g(-1) and 1.401 +/- 0.049 microg g(-1); for 1.5 mm nail with backing: 1.354 +/- 0.054 microg g(-1) and 1.367 +/- 0.068 microg g(-1).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".