Chromium behavior in aquatic environments: a review
Bibliographic record
Abstract
The fate of chromium (Cr) – a redox sensitive metal – in surface sediments is closely linked to early diagenetic processes. This review summarizes the main redox pathways that have been clearly identified over recent decades concerning the behavior of Cr(III,VI) in aquatic environments, and applies them to surface sediments where data for redox speciation remain limited. Overall, abiotic redox reactions that govern the speciation of Cr involve manganese (Mn) (III,IV) (hydr)-oxydes for Cr(III) oxidation, Cr(VI)-reducing species (dissolved iron (Fe) (II) and hydrosulfide (HS) − ), and Cr(VI)-reducing phases (ferrous and sulfide minerals, as well as Fe(II)-bearing minerals). Bacterial activity is also responsible for the redox interconversion between Cr(III) and Cr(VI): biotic reduction of Cr(VI) to Cr(III) is observed through either detoxification or dissimilatory reduction. Whereas Mn(II)-oxidizing bacteria are known to promote indirect oxidation of Cr(III) to Cr(VI), the reaction mechanisms are unresolved. Conversely, oxygen (O 2 ), nitrate (NO 3 − ), and nitrite (NO 2 − ) do not appear to play any role in Cr(III) oxidation. Additionally, Mn(II) and ammonium (NH 4 + ) are not known to promote Cr(VI) reduction. Once reduced, the mobility of Cr(III) in sediments is significantly restricted and regulated by precipitation and sorption processes. Finally, even if the role of natural organic matter in sediment has been determined, further research is required to identify the complexation mechanisms.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".