Farming systems designing landscapes: land management units at the interface between agronomy and geography
Bibliographic record
Abstract
Agriculture faces big challenges, such as feeding a growing population and providing an increasing amount of biomass for energy production. Land is, however, a limited resource and intensification of agricultural practices is deprecated because of the negative impacts on natural resources. Effective answers should therefore be fostered by the development of smarter spatial configurations of agricultural activities. The improvement of farming systems therefore requires agronomy to interact with geography and other disciplines that deal with spatially-explicit aspects of agricultural land management. Different research approaches have supported agronomy in the development of a landscape approach and in this paper we focus on the interactions with geography fostering the enhancement of a common language about the way farming practices are observed and understood by the two disciplines. For this purpose, we compare land management units, identified in recent agronomic literature, with the aim to facilitate future synergies of landscape-oriented research about farming system design. We conclude by arguing for the enhancement of the interface between agronomy and geography and discussing some perspectives on the use of the various land management units in the design of future farming systems with a landscape approach.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".