Assessing the potential long-term increase of oceanic fossil fuel CO <sub>2</sub> uptake due to CO <sub>2</sub> -calcification feedback
Bibliographic record
Abstract
Abstract. Plankton manipulation experiments exhibit a wide range of sensitivities of biogenic calcification to simulated anthropogenic acidification of the ocean, with the "lab rat" of planktic calcifiers, Emiliania huxleyi apparently not representative of calcification generally. We assess the implications of this observational uncertainty by creating an ensemble of realizations of an Earth system model that encapsulates a comparable range of uncertainty in calcification response to ocean acidification. We predict that a substantial reduction in marine carbonate production is possible in the future, with enhanced ocean CO2 sequestration across the model ensemble driving a 4–13% reduction in the year 3000 atmospheric fossil fuel CO2 burden. Concurrent changes in ocean circulation and surface temperatures in the model contribute about one third to the increase in CO2 uptake. We find that uncertainty in the predicted strength of CO2-calcification feedback seems to be dominated by the assumption as to which species of calcifier contribute most to carbonate production in the open 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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".