Lethal by design? Guiding environmental assessments of ocean alkalinity enhancement toward realistic contextualization of the alkalinity perturbation
Bibliographic record
Abstract
Ocean Alkalinity Enhancement (OAE) aims to mitigate climate change by increasing the chemical capacity of seawater to store anthropogenic CO2. OAE can be implemented through multiple pathways, each of which intentionally modifies marine carbonate chemistry through increases in total alkalinity (TA). Experimental research has only recently begun to assess how such TA perturbations (∆TA) affect ocean geochemical processes and ecosystems. Meaningful assessments need context on how ∆TA induced by different OAE pathways would evolve over time and in magnitude. Here, we use a dilution equation, a regional model, and a global model to explore how marine systems and life styles would experience ∆TA under realistic constraints. We find that a more extreme ∆TA of >1000 μmol kg-1, a perturbation commonly considered in OAE experiments, only occurs for minutes in a miniscule fraction of the OAE-perturbed seawater volume. In contrast, ∆TA between 1-100 μmol kg-1 is a ubiquitous perturbation range for OAE under real-world constraints, yet rarely in focus of environmental OAE assessments. These results suggest that there is a disconnect between real-world ∆TA that can plausibly be invoked by OAE and the experimental ∆TA range frequently used in the context of the environmental OAE assessment. While “unrealistic” ∆TA can provide crucial insights into response patterns to OAE, they can also cause overestimation of OAE effects, if the unrealistic ∆TA is not contextualized appropriately. Our results can be used to improve the contextualization of OAE studies, thereby making the interpretation of ∆TA effects on the environment more robust.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".