Le projet Welfare Quality : de l’attente des consommateurs à la mise en place de certifications bien-être en élevage
Bibliographic record
Abstract
In 1999, AGRIBEA was set up to coordinate animal welfare research conducted by INRA (French Institute for Agronomy Research). Initially made up of some forty researchers, AGRIBEA expanded rapidly both within and outside INRA, to include 128 members, of which less than two thirds are from INRA, the other members coming from universities or technical institutes. AGRIBEA organizes scientific seminars every quarter, on topics of general interest focused around animal welfare : pain, emotions, ethics in human-animal relations, etc. AGRIBEA also stimulated new research avenues to address the question of mental states in animals. AGRIBEA improves the visibility of INRA work within the institution, as well as of all French research, thereby helping exchanges within large international research projects.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".