Freshening of the western Arctic negates anthropogenic carbon uptake potential
Bibliographic record
Abstract
Abstract As human activities increase the atmospheric concentration of carbon dioxide (CO2), the oceans are known to absorb a significant portion. The Arctic Ocean has long been considered to have enormous potential to sequester anthropogenic CO2, and mitigate emissions. The frigid waters make CO2more soluble, and as sea ice melts, greater surface area is exposed to absorb CO2. However, sparse data have made quantifying the amount of anthropogenic CO2in the Arctic difficult, stimulating much debate over the basin's contribution to CO2sequestration from the atmosphere. Using three separate cruises in 1994, 2005, and 2015 in the Canada and Makarov basins, we analyze the decadal variability in anthropogenic CO2uptake in the central western Arctic. Here we show, from direct carbon system measurements spanning two decades, that despite increased atmospheric CO2, total dissolved inorganic carbon has actually decreased, with minimal anthropogenic CO2uptake. The reduction in dissolved CO2results from a dilution of total alkalinity by increased freshwater supply, particularly river water. Changes in the freshwater budget of the western Arctic override its uptake potential, resulting in a weak sink, or possibly source of CO2.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".