Reply to Oreska <i>et al</i> ‘Comment on Geoengineering with seagrasses: is credit due where credit is given?’
Bibliographic record
Abstract
In their comment on the review paper, 'Geoengineering with seagrasses: is credit due where credit is given?,' Oreska et al 2018 state that some of the concerns raised in the review 'warrant serious consideration by the seagrass research community,' but they argue that these concerns are either not relevant to the Voluntary Carbon Standard protocol, VM0033, or are already addressed by specific provisions in the protocol. The VM0033 protocol is a strong and detailed document that includes much of merit, but the methodology for determining carbon sequestration in sediment is flawed, both in the carbon stock change method and in the carbon burial method. The main problem with the carbon stock change method is that the labile carbon in the surface layer of sediments is vulnerable to remineralization and resuspension; it is not sequestered on the 100 year timescale required for carbon credits. The problem with the carbon burial method is chiefly in its application. The protocol does not explain how to apply 210 Pb-dating to a core, leaving project proponents to apply the inappropriate methods frequently reported in the blue carbon literature, which result in overestimated sediment accumulation rates. Finally, the default emission factors permitted by the protocol are based on literature values that are themselves too high. All of these problems can be addressed, which should result in clearer, more rigorous guidelines for awarding carbon credits for the protection or restoration of seagrass meadows.
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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 | 0.022 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.063 | 0.065 |
| Insufficient payload (model declined to judge) | 0.016 | 0.020 |
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".