Ballasting by cryogenic gypsum enhances carbon export in a Phaeocystis under-ice bloom
Bibliographic record
Abstract
Abstract Mineral ballasting enhances carbon export from the surface to the deep ocean; however, little is known about the role of this process in the ice-covered Arctic Ocean. Here, we propose gypsum ballasting as a new mechanism that likely facilitated enhanced vertical carbon export from an under-ice phytoplankton bloom dominated by the haptophyte Phaeocystis. In the spring 2015 abundant gypsum crystals embedded in Phaeocystis aggregates were collected throughout the water column and on the sea floor at a depth below 2 km. Model predictions supported by isotopic signatures indicate that 2.7 g m−2 gypsum crystals were formed in sea ice at temperatures below −6.5 °C and released into the water column during sea ice melting. Our finding indicates that sea ice derived (cryogenic) gypsum is stable enough to survive export to the deep ocean and serves as an effective ballast mineral. Our findings also suggest a potentially important and previously unknown role of Phaeocystis in deep carbon export due to cryogenic gypsum ballasting. The rapidly changing Arctic sea ice regime might favour this gypsum gravity chute with potential consequences for carbon export and food partitioning between pelagic and benthic ecosystems.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".