Comment on egusphere-2025-2443
Bibliographic record
Abstract
Abstract. The boron isotopic composition of planktonic foraminifera is a powerful tool to reconstruct ocean pH and CO2 in the past. Applications to the high-latitude and polar oceans are however limited as robust calibrations between the δ11B of foraminifera and ocean pH in these regions are lacking. Here, we present a new empirical calibration for the high latitude Arctic species Neogloboquadrina pachyderma and the sub-polar to temperate species Neogloboquadrina incompta using towed specimens from the Labrador Sea, Baffin Bay, and the Nordic Seas. When paired with in situ hydrographic data, this approach allows us to avoid key assumptions used in traditional core top calibrations that are required to link shell geochemical composition to hydrographic conditions during their formation. We show that the foraminifera δ11B of the species analysed is well correlated with the δ11B of seawater borate ion. Further, the foraminiferal δ11B values are consistently lower than seawater equilibrium borate values, consistent with the interpretation of more acidic seawater in the microenvironment due to respiration. However, unlike published calibrations for non-spinose species to date the slope of the δ11B foraminifera to δ11B borate calibration is >1. We discuss several drivers of this higher sensitivity to pH and describe the possible role of vital effects in determining the boron isotopic composition of N. pachyderma and N. incompta. Finally, we apply the tow calibration to core top samples from the Nordic Seas to validate the calibration for use in the paleorecord.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.005 |
| Insufficient payload (model declined to judge) | 0.630 | 0.470 |
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".