Establishment of Grass Strips for Maintaining Biodiversity in Agroecosystems
Bibliographic record
Abstract
Main principle of the common agricultural policy of European Union is achievement of high results with the least possible negative impact on the environment, land protection and efficient use of natural resources. For that purpose, a number of studies are carried out, related to the improvement of biodiversity and protection of the pollinators in the areas of production. Two type of grass mixes were observed: “Laitamag” (Hungary) composed of White mustard (Sinapis alba L.), White clover (Trifolium repens L.), Phacelia (Phacelia tanacetifolia Bentham), Crimson clover (Trifolium incarnatum L.), Egyptian clover (Trifolium alexandrinum L.), Red clover (Trifolium pretense L.), Wild oats (Avena sativa L.), Alfalfa (Medicago sativa L.), Buckwheat (Fagopyrum esculentum Moench) and Sainfoin (Onobrychis viciifolia Scop.) and a mix, proposed by the Agrarian University: White mustard (Sinapis alba L.), White clover (Trifolium repens L.), Phacelia (Phacelia tanacetifolia Bentham), Buckwheat (Fagopyrum esculentum Moench), Coriander (Coriandrum sativum L.). The vegetation of the autumn crops began in March, as the blossoming lasts for 60-63 days, from the beginning of April until 24 June. For the spring sowing (18 March), the flowering of the mixes occurred later, in the second 10-day period of May and ended at the end of June. As a result of the low temperatures during winter, the white mustard, buckwheat and sainfoin plants perished. White clover proves to be the most resilient species.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".