Shelf-to-basin shuttle of highly fractionated chromium isotopes in the Arctic Ocean
Bibliographic record
Abstract
The oceanic chromium (Cr) cycle is mainly governed by the interconversion and the distribution of Cr(VI) and Cr(III) species and their stable isotopic ratios (δ 53 Cr) in the water column. As a result, the Cr cycle generates a strong correlation between the natural logarithm of its dissolved concentration and δ 53 Cr regardless of the location of sampling. A few studies have reported the Cr composition of certain regions falling off the global Cr array, highlighting the local prevalence of underlying mechanisms participating in the Cr cycle in the oceans. In an effort to better constrain the global Cr array, this study presents an extensive dataset for total dissolved Cr concentration ([Cr] T ) and δ 53 Cr in the Arctic Ocean in regions meeting the environmental conditions where Cr was observed to fall off the global Cr array (e.g. continental shelves, restricted water circulation, sea ice melting). We find that more than 70% of the Arctic seawater collected plot below the global Cr array due to a small addition of highly fractionated Cr (−2.8 ‰ to −1.1 ‰) and its transport across all the Arctic regions sampled. We identify the Chukchi Shelf as the region where highly fractionated Cr is produced, from where a Cr shuttle could work in tandem with the Arctic Fe and Mn shuttles to explain the production and widespread export of isotopically light Cr in the Arctic waters. We identify a second non-reductive release of highly fractionated Cr in the Canadian Arctic Archipelago, Baffin Bay and potentially the Labrador Sea via sediment resuspension, alongside addition of isotopically light Cr originating from crustal rocks. These findings demonstrate that the Arctic-modified outflow signature of Cr isotopes modify the Cr isotopic signature of the North Atlantic waters, and that the North Atlantic waters may deviate from the global Cr array depending on whether the isotopically light Cr added to the Arctic Ocean is Cr(III) that has not been scavenged or Cr(III) that has oxidized to 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".