Solid and liquid state speciation of chromium of relevance for health
Bibliographic record
Abstract
The chemical form (chemical speciation) of chromium (Cr) is important for human health. Hexavalent Cr (Cr VI ), present as oxyanions in water, is of great concern even at trace levels. Here, we briefly describe and discuss common and additional liquid state (often standardized) and solid state Cr speciation methods for typical samples of health concerns. This review covers common standardized, extraction-based liquid state methods and various solid state Cr speciation methods. Liquid state methods include chromatography, colorimetric methods, mass spectrometry, and electrochemical methods, with widely varying detection limit ranges to accommodate all sample needs. The most sensitive liquid state method can detect trace amounts of Cr VI in the nanograms per litre range. Colorimetric methods can be used both for the liquid and solid state and are the simplest methods without the need for a laboratory or equipment. Other solid state methods include vibrational spectroscopy, electrochemical methods, and various laboratory- or synchrotron-based methods: X-ray photoelectron spectroscopy, X-ray absorption spectroscopy, and X-ray diffraction. No method is perfect on its own, and we therefore recommend best practices, the investigation of potential interfering agents, and validating the method with another method. However, the largest threat to accurate Cr speciation-based hazard assessments is the dynamic change of Cr speciation in a potential exposure scenario or during sample preparation for the analytical method. To avoid wrong conclusions, we recommend considering the Cr chemistry, the sample chemistry, and the method-specific interferences and detection limits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".