Deciphering the Signal of Arctic Climate Change
Bibliographic record
Abstract
Whether or not Arctic regions remain(ed) a carbon sink or source to the atmosphere during rapidly warming climates (in the past) is a fundamental question with regards to future global warming and ocean acidification. The boron isotopic composition of planktonic foraminiferal shell calcite (δ11BCc) can potentially provide valuable information of past seawater pH if information on a second carbonate system parameter, temperature, and salinity is available. However, most applications of palaeoceanographic proxies to the cold polar oceans are limited due to a paucity of calibration data, limited information on the calcification habitat, and secondary effects of the carbonate system on the temperature recorded by Mg/Ca values measured in the dominant Arctic species Neogloboquadrina pachyderma sinistral (NPS). Here we present a new Multi-Collector Inductively Coupled Mass Spectrometry (MC-ICPMS) δ11B dataset measured on live NPS collected via plankton tows from the Labrador Sea and Baffin Bay. We compare our results with δ11Bborate derived from pH measurements, δ13C DIC seawater values, temperature and salinity collected at the time and depth the foraminifera calcified. To quantify the control of low carbonate ion concentration on Mg/Ca derived temperatures we measured B/Ca alongside Mg/Ca in the calibration dataset. We are thus able to present a new geochemical correction scheme that can isolate non-thermal controls on the Mg/Ca-temperature relationship for NPS, allowing us for the first time the reconstruction of carbonate system parameters in the Arctic Ocean.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".