Impact of sea ice variability on the oxygen isotope content of seawater under glacial and interglacial conditions
Bibliographic record
Abstract
Records of temporal variability in the oxygen isotopic composition of biogenic carbonates (δ18Oc) from ocean sediment cores inform our understanding of past continental ice volume and ocean temperatures. Interpretation of δ18Ocvariability typically neglects changes due to factors other than ice volume and temperature. Here we investigate whether glacial‐interglacial changes in sea ice, which fractionates seawater during its formation, could shift the isotopic value of seawater—in the deep ocean (affecting benthic foraminiferal δ18Oc and thereby potentially impacting oxygen isotope based sea level reconstructions) or in surface waters (affecting planktic foraminiferal δ18Oc). We simulate glacial and interglacial states with the isotope‐enabled University of Victoria Earth System Climate Model and perform a global analysis. Distinct patterns of sea ice production emerge for the glacial versus interglacial states. We find no substantive shift in δ18Ow in model deep or bottom waters due to the simulated interglacial‐glacial sea ice variability. Small isotopic shifts due to sea ice variability are concentrated in the model's surface waters of the Northern Hemisphere, specifically in the Labrador Sea and northeastern North Atlantic.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".