Concevoir et expérimenter des vergers agroforestiers en Agriculture Biologique (VERtiCAL).
Bibliographic record
Abstract
The VERtiCAL research project focused from 2013 to 2018 on the spatial and temporal diversification of fruit tree systems as a relevant mean for reducing pesticide use. The project resulted in the design and assessment of two fruit agroforestry systems (AFS), called "TAB" and "Durette", managed in organic farming and with specific technical and economic characteristics. The project allowed co-design experiences and led to the development of a new tool for ex ante assessment of AFS. First results show a 52% reduction of pesticides on the TAB system compared to a conventional reference system while reaching yield objectives, and a very low reliance to pesticides on the Durette system. As for biodiversity, specific richness of birds increased from 12 to 24 species on the Durette system, from 24 to 35 on the TAB system. Spatial planning fulfills the working organization, but does not make it possible to fully control pests yet. Results will be consolidated in the continuing EMPUSA project (2019-2025). Both sites are now important demonstration sites for farmers and agricultural advisors interested in implementing AFS.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".