A Mg(OH)<sub>2</sub> coprecipitation method for determining chromium speciation and isotopic composition in seawater
Bibliographic record
Abstract
Abstract Chromium (Cr) stable isotopes have emerged as a powerful tool for tracking environmental redox transformations. This is because Cr isotopes are fractionated during redox reactions between Cr(III) and Cr(VI). In order to fully exploit the information recorded within Cr isotope compositions, we must be able to track changes in Cr speciation throughout the environment and, in particular, the changes in speciation between input to the ocean and eventual deposition in sediments. We must also be able to access the isotope compositions of each Cr species, rather than only total dissolved Cr. We have thus developed a magnesium hydroxide coprecipitation method that meets these objectives. This method achieves complete recovery and has a typical precision on concentration measurements of ±8% (1σ). It was tested using seawater collected from Saanich Inlet, a persistently anoxic fjord on the Pacific coast of Canada. Chromium speciation profiles and proof‐of‐concept isotope ratio measurements on selected samples indicate that isotopically lighter Cr(III) can be isolated from coexisting isotopically heavier Cr(VI), effectively resolving species‐specific Cr isotope compositions. While the oxygenated surface waters of Saanich Inlet follow the generally observed correlation between seawater Cr concentration and its isotopic composition, seawater from anoxic depths diverges from this array, indicating that different processes are responsible for setting the isotope composition of these deeper waters. Broader application of Mg(OH)2 coprecipitation has strong potential to yield new insights into the fractionation of Cr isotopes in the oceans and the pathways that ultimately set the Cr isotopic composition of marine sediments and sedimentary archives.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".