Last interglacial global mean sea level from high-precision U-series ages of Bahamian fossil coral reefs
Bibliographic record
Abstract
Accurate characterization of Last Interglacial (MIS 5e; ∼129–116 ka) sea level is important for understanding ice sheet sensitivity to climate change, with implications for predicting future sea-level rise. Here we present a record of MIS 5e sea level based on high-precision U-series ages of 23 corals with precise elevation measurements from reefs around Crooked Island, Long Cay, Long Island, and Eleuthera, The Bahamas. Rigorous screening criteria identified the most pristine samples, and nearly all samples show a narrow δ234Uinitial range between 143.8 and 151.3‰. We infer global mean sea level (GMSL) from these local observations by correcting them for glacial isostatic adjustment (GIA) and long-term subsidence. For GIA, we consider a range of ice histories and Earth viscosity structures. We identify, via Bayesian inference, the range of isostatic and GMSL histories that are consistent with MIS 5e observations across The Bahamas. When applying an open-system correction to our ages, we find that MIS 5e GMSL likely peaked higher than 1 m, but very unlikely exceeded 2.7 m. Our posterior GMSL is lower than previous estimates, but consistent with recent results of modeling and observations. Additionally, sea level observations at other locations (Seychelles, Western Australia, Yucatan) are only slightly above/within the 95% range of predicted local sea level, i.e., GIA plus GMSL, for our open-system/closed-system results. Our relatively constant MIS 5e GMSL indicates that Greenland and Antarctica melted beyond their present extents and, given the insolation forcing, that their contributions to GMSL were likely out-of-phase. These results indicate that the ice sheets may be very sensitive to regional temperature, which has important implications for their combined impact on global sea levels at a time when greenhouse gases increases are causing simultaneous warming at both poles.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".