Sea surface <i>p</i>CO<sub>2</sub> cycles and CO<sub>2</sub> fluxes at landfast sea ice edges in Amundsen Gulf, Canada
Bibliographic record
Abstract
In late fall, spring, and early summer, we measured the surface ocean and atmospheric partial pressures of CO2 (pCO2sw and pCO2atm, respectively) to calculate CO2 gradients (ΔpCO2 = pCO2sw − pCO2atm) and resulting fluxes along the landfast ice regions of southern Amundsen Gulf, Canada. In both the fall and spring seasons we observed positive ΔpCO2caused by wind‐driven upwelling. The presence of a landfast ice edge appeared to be an important factor in promoting this upwelling in some instances. Despite the potential for significant CO2 evasion, we calculated small fluxes during these periods due to high sea ice concentration. In summer, ΔpCO2 became strongly negative across the entire study area. Primary production no doubt played a role in the pCO2swdrawdown, but we found evidence that sea ice melt and dissolution of ice‐bound calcium carbonate crystals may also have been contributing factors. The seasonal ΔpCO2 cycle suggests a net annual sink of atmospheric CO2 for these landfast ice regions, since calculated summer uptake by the ocean was much stronger than fall/spring outgassing and occurred over a longer time period. However, we hypothesize that this balance is highly dependent on the strength of upwelling and the timing of ice formation and decay, and therefore may be influenced by interannual variability and the effects of climate change.
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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 | 0.000 |
| 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".