Soil Health and Related Ecosystem Services in Organic Agriculture
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
<p>Soil health is dependent upon complex bio-physical and bio-chemical processes which interact in space and time. Microrganisms and fauna in soil comprise highly diverse and dynamic communities that contribute, over either short or long time frames, to the transformation of geological minerals and release of essential nutrients for plant growth. Certified organic soil management practices generally restrict the use of chemically-processed highly soluble plant nutrients, leading to dependence on nutrient sources that require microbial transformation of poorly soluble geological minerals. Consequently, slow release of nutrients controls their rate of uptake by plants and associated plant physiological processes. Microbial and faunal interactions influence soil structure at various scales, within and between crystalline mineral grains, creating complex soil pore networks that further influence soil function, including the nutrient release and uptake by roots. The incorporation of organic matter into soil, as either manure or compost in organic farming systems is controlled to avoid excessive release of soluble nutrients such as nitrogen and phosphorus, while simultaneously contributing an essential source of carbon for growth and activity of soil organisms. The interdependence of many soil physical and chemical processes contributing to soil health is strongly linked to activities of the organisms living in soil as well as to root structure and function. Capitalizing on these contributions to soil health cannot be achieved without holistic, multiscale approaches to nutrient management, an understanding of interactions between carbon pools, mineral complexes and soil mineralogy, and detailed examination of farm nutrient budgets.</p>
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it