Rapid Changes in Anthropogenic Carbon Storage and Ocean Acidification in the Intermediate Layers of the Eurasian Arctic Ocean: 1996–2015
Bibliographic record
Abstract
The extended multiple linear regression technique is used to determine changes in anthropogenic carbon in the intermediate layers of the Eurasian Basin based on occupations from four cruises between 1996 and 2015. The results show a significant increase in basin‐wide anthropogenic carbon storage in the Nansen Basin (0.44–0.73 ± 0.14 mol C·m−2·year−1) and the Amundsen Basin (0.63–1.04 ± 0.09 mol C·m−2·year−1). Over the last two decades, inferred changes in ocean acidification (0.020–0.055 pH units) and calcium carbonate desaturation (0.05–0.18 units) are pronounced and rapid. These results, together with results from carbonate‐dynamic box model simulations and 129I tracer distribution simulations, suggest that the accumulation of anthropogenic carbon in the intermediate layers of the Eurasian Basin are consistent with increasing concentrations of anthropogenic carbon in source waters of Atlantic origin entering the Arctic Ocean followed by interior transport. The dissimilar distributions of anthropogenic carbon in the interior Nansen and Amundsen Basins are likely due to differences in the lateral ventilation of the intermediate layers by the return flows and ramifications of the boundary current along the topographic boundaries in the Eurasian Basin.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".