Impact of sea‐ice processes on the carbonate system and ocean acidification at the ice‐water interface of the Amundsen Gulf, Arctic Ocean
Bibliographic record
Abstract
From sea‐ice formation in November 2007 to onset of ice melt in May 2008, we studied the carbonate system in first‐year Arctic sea ice, focusing on the impact of calcium‐carbonate (CaCO 3 ) saturation states of aragonite (ΩAr) and calcite (ΩCa) at the ice‐water interface (UIW). Based on total inorganic carbon (C T ) and total alkalinity (A T ), and derived pH, CO 2 , carbonate ion ([CO 3 2− ]) concentrations and Ω, we investigated the major drivers such as brine rejection, CaCO 3 precipitation, bacterial respiration, primary production and CO 2 ‐gas flux in sea ice, brine, frost flowers and UIW. We estimated large variability in sea‐ice C T at the top, mid, and bottom ice. Changes due to CaCO 3 and CO 2 ‐gas flux had large impact on C T in the whole ice core from March to May, bacterial respiration was important at the bottom ice during all months, and primary production in May. It was evident that the sea‐ice processes had large impact on UIW, resulting in a five times larger seasonal amplitude of the carbonate system, relative to the upper 20 m. During ice formation, [CO 2 ] increased by 30 µmol kg −1 , [CO 3 2− ] decreased by 50 µmol kg −1 , and the ΩAr decreased by 0.8 in the UIW due to CO 2 ‐enriched brine from solid CaCO 3 . Conversely, during ice melt, [CO 3 2− ] increased by 90 µmol kg −1 in the UIW, and Ω increased by 1.4 between March and May, likely due to CaCO 3 dissolution and primary production. We estimated that increased ice melt would lead to enhanced oceanic uptake of inorganic carbon to the surface layer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".