Technical note: Ocean Alkalinity Enhancement Pelagic Impact Intercomparison Project (OAEPIIP)
Bibliographic record
Abstract
Abstract. Ocean Alkalinity Enhancement (OAE) aims to transfer carbon dioxide (CO2) from the atmosphere to the ocean by increasing the capacity of seawater to store CO2. The potential effects of OAE-induced changes in seawater chemistry on marine biology must be assessed to understand if OAE, operated at a climate relevant scale, would be environmentally sustainable. Here, we describe the design of the Ocean Alkalinity Enhancement Pelagic Impact Intercomparison Project (OAEPIIP) – a standardised OAE microcosm experiment with plankton communities to be conducted worldwide. OAEPIIP provides funding for participating laboratories to conduct OAE experiments in their local environments. This paper constitutes a detailed manual on the standardised methodology that shall be adopted by all OAEPIIP participants. The individual studies will provide new insights into how plankton communities respond to OAE. The synthesis of these standardized studies, without publication bias, will reveal common OAE-responses that occur across geographic and environmental gradients and are therefore particularly important to determine. The funding available to OAEPIIP and resulting data will be shared to maximise its value and the accessibility. The globally coordinated effort has potential to promote scientific consensus about the potential effects of OAE on diverse plankton communities. Such consensus, through inclusion of the global community, will provide a sounder base to facilitate political decision making whether OAE should be upscaled or not.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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; both teacher heads agree on what is shown here.
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".