Using chemical speciation modelling to discuss variations in patch test reactions to different aluminium and chromium salts
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
BACKGROUND: Allergic contact dermatitis to metals is diagnosed by applying a metal salt in a patch test. The bioavailability of the metal salt might depend on the choice of metal salt, the concentration, sweat composition, and pH. OBJECTIVES: The main purpose of this study was to apply chemical speciation modelling, which is based on experimentally derived input data and calculates the concentrations of chemical forms (species) in solutions, to reproduce and discuss clinical patch test results of aluminium and chromium. METHODS: Joint Expert Speciation System (JESS), Hydra/Medusa, and Visual MINTEQ were employed to study the bioavailable fraction and chemical form of clinically applied aluminium and chromium salts as a function of salt type, applied concentration, sweat composition, and pH. RESULTS: Investigated aluminium and chromium salts can have a very low bioavailability with a large dependency on sweat composition, pH, metal salt, and concentration. Both aluminium and chromium ions could shift the pH towards acidic or basic values based on their chemical form. CONCLUSIONS: Reported seasonal and interpatient variability in positive reactions to aluminium is likely related to sweat pH and composition. Potassium dichromate increases the pH, whereas aluminium and trivalent chromium chloride strongly decrease the pH, possibly increasing skin diffusion.
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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 | 0.000 | 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 | 0.000 |
| 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