MétaCan
Menu
Back to cohort
Record W4415752309 · doi:10.1139/cjc-2025-0118

Solid and liquid state speciation of chromium of relevance for health

2025· article· en· W4415752309 on OpenAlexafffundvenue
Yolanda S. Hedberg, Mark C. Biesinger, Zhiqiang Wang

Bibliographic record

VenueCanadian Journal of Chemistry · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicChromium effects and bioremediation
Canadian institutionsQueen's UniversityWestern University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaWestern University
KeywordsHexavalent chromiumChromiumGenetic algorithmDetection limitElectrochemistrySolid-stateLiquid stateAnalytical Chemistry (journal)Sample preparation

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.160

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.244
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of ChemistrySame topicChromium effects and bioremediationFrench-language works237,207