A Model‐Based Analysis of Physical and Biogeochemical Controls on Carbon Exchange in the Upper Water Column, Sea Ice, and Atmosphere in a Seasonally Ice‐Covered Arctic Strait
Bibliographic record
Abstract
Abstract In this study, we consider a 1‐D model incorporating both sea ice and pelagic systems in order to assess the importance of various processes on the vertical transport and exchange of carbon in the seasonally ice‐covered marine Arctic. The model includes a coupled ice‐ocean ecosystem, a parameterization of ikaite precipitation and dissolution, a formulation for ice‐air carbon exchange, and a formulation for brine rejection and freshwater dilution of dissolved inorganic carbon (DIC) and total alkalinity (TA) associated with ice growth and melt. Sensitivity analyses illustrate that (1) the pelagic ecosystem accounts for more than half of the net ocean carbon uptake, but ice algae have little effect on the air‐sea exchange in the standard run; (2) inclusion of ikaite precipitation and dissolution do not strongly affect the net ocean carbon uptake for concentrations within the observed range but can become important for larger concentrations; (3) varying DIC and TA in the ice by equal amounts, or varying brine deposition depth, does not affect the net ocean carbon uptake, because the coincident changes in TA and DIC concentrations at the sea surface serve to counteract one another with respect to sea surface pCO2; and (4) the proportions of carbon released to the water column (versus to the atmosphere) during ice growth and melt are important quantities to constrain in order to determine the contribution of the combined ice‐ocean system to oceanic uptake of atmospheric carbon.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".