Bibliographic record
Abstract
Continental shelves are thought to be affected disproportionately by climate change and are a large contributor to global air–sea carbon dioxide (CO 2 ) fluxes. It is often reported that low-latitude shelves tend to act as net sources of CO 2 , whereas mid- and high-latitude shelves act as net sinks. Here, we combine a high-resolution regional model with surface water time series and repeat transect observations from the Scotian Shelf, a mid-latitude region in the northwest North Atlantic, to determine what processes are driving the temporal and spatial variability of partial pressure of CO 2 ( p CO 2 ) on a seasonal scale. In contrast to the global trend, the Scotian Shelf acts as a net source. Surface p CO 2 undergoes a strong seasonal cycle with an amplitude of ∼ 200–250 µ atm. These changes are associated with both a strong biological drawdown of dissolved inorganic carbon (DIC) in spring (corresponding to a decrease in p CO 2 of 100–200 µ atm) and pronounced effects of temperature, which ranges from 0 ∘ C in the winter to near 20 ∘ C in the summer, resulting in an increase in p CO 2 of ∼ 200–250 µ atm. Throughout the summer, events with low surface water p CO 2 occur associated with coastal upwelling. This effect of upwelling on p CO 2 is also in contrast to the general assumption that upwelling increases surface p CO 2 by delivering DIC-enriched water to the surface. Aside from these localized events, p CO 2 is relatively uniform across the shelf. Our model agrees with regional observations, reproduces seasonal patterns of p CO 2 , and simulates annual outgassing of CO 2 from the ocean of + 1.7 ± 0.2 mol C m −2 yr −1 for the Scotian Shelf, net uptake of CO 2 by the ocean of - 0.5 ± 0.2 mol C m −2 yr −1 for the Gulf of Maine, and uptake by the ocean of - 1.3 ± 0.3 mol C m −2 yr −1 for the Grand Banks.
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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 | 0.003 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.030 | 0.025 |
| Insufficient payload (model declined to judge) | 0.181 | 0.152 |
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".