Efficiences technique et environnementale en agriculture : le cas du bassin de la rivière Chaudière au Québec
Bibliographic record
Abstract
Malgre l’imposition de normes environnementales strictes au Quebec, l’impact des activites agricoles sur la qualite de l’eau demeure preoccupant notamment dans la region de Chaudiere-Appalaches. Cette region est intensive en productions animale et vegetale ce qui entraine des surplus de phosphore, d’azote et de sediments. Cette etude a pour objectif que d’analyser l’efficience technique et l'efficience environnementale des producteurs agricoles du bassin de la riviere Chaudiere localise au Sud de la ville de Quebec. Nous adoptons une approche stochastique parametrique appliquee aux fonctions de distance. Les donnees utilisees portent sur 210 fermes agricoles et les resultats obtenus montrent qu’il existe une forte correlation entre les deux efficiences. De plus, comme le montrent d’autres etudes, la performance environnementale entraine des couts additionnels au niveau des exploitations agricoles.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".