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
The defining challenge of sustainable agriculture is the production of food and other agricultural products at an environmental cost that does not jeopardize the food security and general welfare of future generations. Feeding another three billion people in the face of climate change, biodiversity loss, and an environment already saturated with excess nitrogen and other reactive pollutants requires new approaches and new tools in the design and deployment of workable solutions. Solutions will be local but all will require an ecological systems approach that considers sustainable farming practices in the full context of ecosystems and landscapes. And their deployment will require an understanding of the social systems capable of building incentives that produce socially desired outcomes. Socioecological models for agriculture provide an opportunity to explore feedbacks, trade-offs, and synergies that can optimize and strengthen emerging connections between farming and society. With the right incentives, innovative research, and political will, a sustainable agriculture is within our reach.
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 | 0.000 | 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) | 0.001 | 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 it