Evidence that low‐temperature oceanic hydrothermal systems play an important role in the silicate‐carbonate weathering cycle and long‐term climate regulation
Bibliographic record
Abstract
The feedbacks between changes in atmospheric CO2 levels, climate, and CO2 drawdown into rocks are incompletely understood. In particular, the role of the upper oceanic crust in this long‐term carbon cycling is debated. Here, a simple model for the precipitation of calcite in the upper oceanic crust is developed with the aim of understanding why Late Mesozoic upper oceanic crust contains several times higher CO2 concentrations (~2.5 wt%) than Cenozoic upper oceanic crust (~0.5 wt%). The modeling shows that neither heating of seawater, nor leaching of Ca from the rock with charge balance maintained by Mg uptake by the rock, can lead to >0.2 wt% CO2 uptake by the oceanic crust. Alkalinity production during fluid‐rock reaction in the crust allows substantially more CO2 to be taken up by the crust in calcite, and is consistent with changes in the major element composition of Late Mesozoic upper oceanic crust due to hydrothermal alteration. The higher CO2 content of Late Mesozoic than Cenozoic upper oceanic crust thus requires greater alkalinity production by fluid‐rock reactions in the Late Mesozoic. This may have been due to higher bottom water temperature and/or seawater having a different composition leading to different secondary minerals forming in the Late Mesozoic. Irrespective of the mechanism, the negative feedback on atmospheric CO2 levels provided by enhanced hydrothermal CO2 consumption in the Late Mesozoic was of similar magnitude to that from continental weathering.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".