Metrics that matter for assessing the ocean biological carbon pump
Bibliographic record
Abstract
The biological carbon pump (BCP) comprises wide-ranging processes that set carbon supply, consumption, and storage in the oceans’ interior. It is becoming increasingly evident that small changes in the efficiency of the BCP can significantly alter ocean carbon sequestration and, thus, atmospheric CO 2 and climate, as well as the functioning of midwater ecosystems. Earth system models, including those used by the United Nation’s Intergovernmental Panel on Climate Change, most often assess POC (particulate organic carbon) flux into the ocean interior at a fixed reference depth. The extrapolation of these fluxes to other depths, which defines the BCP efficiencies, is often executed using an idealized and empirically based flux-vs.-depth relationship, often referred to as the “Martin curve.” We use a new compilation of POC fluxes in the upper ocean to reveal very different patterns in BCP efficiencies depending upon whether the fluxes are assessed at a fixed reference depth or relative to the depth of the sunlit euphotic zone (Ez). We find that the fixed-depth approach underestimates BCP efficiencies when the Ez is shallow, and vice versa. This adjustment alters regional assessments of BCP efficiencies as well as global carbon budgets and the interpretation of prior BCP studies. With several international studies recently underway to study the ocean BCP, there are new and unique opportunities to improve our understanding of the mechanistic controls on BCP efficiencies. However, we will only be able to compare results between studies if we use a common set of Ez-based metrics.
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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 | 0.013 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".