Analysis of Hexavalent Chromium in Cement Samples from Countries within and outside the EU: A Study from the International Contact Dermatitis Research Group
Bibliographic record
Abstract
Abstract: Background: Allergic contact dermatitis (ACD) caused by hexavalent chromium (Cr(VI)) is often severe and difficult to treat. The content of Cr(VI) in cement can be reduced by, for example, addition of iron(II) sulfate. Since 2005 the content of Cr(VI) in cement is regulated in the EU Directive 2003/53/EC and must not exceed 2 ppm. Since this regulation came into force, ACD caused by cement has markedly been reduced. Objective: To investigate Cr(VI) and total chromium content in samples of cement from countries within and outside the EU. Methods: The members of the International Contact Dermatitis Research Group (ICDRG) were invited to participate in the study with the aim to collect cement samples from geographically different areas. The content of Cr(VI) in the samples was estimated by the diphenyl carbazide spot test, atomic absorption spectroscopy was used to assess the total chromium content. Results: Forty-five cement samples were analyzed, containing amounts of Cr(VI) from <0.1 to >70 ppm. Twenty-one samples contained >2 ppm Cr(VI), 24 contained less. Four of 17 samples from within the EU contained >2 ppm Cr(VI), that is, higher amounts than stipulated in the EU directive, as compared with 17 samples from countries outside the EU. Conclusion: In countries outside the EU, significantly more cement samples contained >2 ppm Cr(VI).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".