Bibliographic record
Abstract
Biological activities that sequester carbon create CO2 offset credits that could obviate the need for reductions in fossil fuel use. Credits are earned by storing carbon in terrestrial ecosystems and wood products, although CO2 emissions are also mitigated by delaying deforestation, which accounts for one-quarter of anthropogenic CO2 emissions. However, non-permanent carbon offsets from biological activities are difficult to compare with each other and with emissions reduction because they differ in how long they prevent CO2 from entering the atmosphere. This is the duration problem. It results in uncertainty and makes it hard to determine the legitimacy of biological activities in mitigating climate change. Measuring, verifying and monitoring the carbon sequestered in sinks greatly increases transaction costs and leads to rent seeking by sellers of dubious sink credits. While biological sink activities undoubtedly help mitigate climate change and should not be neglected, it is shown that there are limits to the substitutability between temporary offset credits from these activities and emissions reduction, and that this has implications for carbon trading. A possible solution to inherent incommensurability between temporary and permanent credits is also suggested.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".