To close the yield-gap while saving biodiversity will require multiple locally relevant strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing yield has emerged as the most prominent element in strategies to deal with growing global demand for food and fibre. It is usually acknowledged that this needs to be done while minimising harm to the environment, but historically land-use intensification has been a major driver of biodiversity loss. The risk is now great that a singular focus on increasing yields will divert attention from the linked problem of biodiversity decline, and the historical pattern will continue. There are options that increase yields while reducing harm to biodiversity, which should be the focus of future strategies. The solutions are not universal, but are locally specific. This is because landscapes vary greatly in inherent biodiversity, the production systems they can support, and the potential for them to be adopted by landholders. While new production techniques might apply at local scale, biodiversity conservation inevitably requires strategies at landscape and larger scales.
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.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.008 |
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 it