A novel approach to dissolution correction of Mg/Ca–based paleothermometry in the tropical Pacific
Bibliographic record
Abstract
Mg/Ca in planktonic foraminifers carries two main signals: calcification temperature and postdepositional test dissolution. Shell dissolution thus distorts water temperature reconstructions made with Mg/Ca in foraminifers. This problem could be resolved by quantifying the impact of carbonate dissolution on Mg/Ca with an independent, temperature‐insensitive deep‐sea calcite dissolution proxy, such as the Globorotalia menardii fragmentation index (MFI). To test the validity of this approach, we measured Mg/Ca in the tests of several planktonic foraminifers and MFI in core tops collected over a wide geographic region of the tropical Pacific and covering a wide range of deep‐sea calcite dissolution and seawater temperature. We confirm that Mg/Ca from different species have different susceptibility to temperature and dissolution. Mg/Ca in surface‐dwelling Globigerina bulloides is controlled by calcification temperature and is largely unaffected by carbonate dissolution estimated from MFI. In contrast, Mg/Ca in deeper dwelling G. menardii is minimally sensitive to temperature and dominantly affected by dissolution. Mg/Ca in Neogloboquadrina dutertrei and Pulleniatina obliquiloculata are significantly affected by both temperature and dissolution, and MFI can be effectively used to correct temperature estimates from these species for calcite dissolution. Additional variables besides temperature and dissolution appear to control Mg/Ca in Globorotalia tumida, and their identification is a prerequisite for interpreting elemental shell composition in this species. Combining down‐core measurements of Mg/Ca in multiple foraminifer species with MFI provides a powerful tool for reconstructing past changes in the upper water column temperature structure in the tropical Pacific.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".