Envisioning the manureshed: Toward comprehensive integration of modern crop and animal production
Bibliographic record
Abstract
The specialization and intensification of agriculture have produced incredible gains in productivity, quality, and availability of agricultural commodities but have resulted in the separation of crop and animal production. A by-product of this separation has been the accumulation of manure regions where animal production is concentrated. Enter the "manureshed," an organizing framework for integrating animal and crop production where budgeting of manure nutrients is used to strategically guide their recycling and reuse in agricultural production systems where manure resources are of highest value. To move beyond regional nutrient balance analyses into the transformational realm required to mitigate "wicked" manure problems, manureshed management requires recognition of the challenges to systematically reorganizing resource flows. In better integrating crop and livestock systems, manureshed management must account for the unique nature of managing manure nutrients within individual livestock industries, anticipate trade-offs in substituting manure for commercial fertilizer, promote technologies to refine manure, and engage extensive social networks across scales that range from the farmgate to nation and beyond.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".