Contribution de l’ergotoxicologie à une prévention construite en agriculture. Rétro-réflexion à partir de trois recherches interventions
Bibliographic record
Abstract
Cette contribution porte sur l’analyse de situations d’exposition aux pesticides à partir de trois études de cas en agriculture (Garrigou et al., 2011; Albert et al., 2021; Fredj, 2021). Elle s’appuie sur les cadres théoriques de la sécurité (sécurité industrielle, ou encore de la psychologie et de l’ergonomie) afin d’identifier des conditions du développement d’une prévention construite et durable. Les cas présentés porteront sur la réglementation encadrant l’usage des produits phytopharmaceutiques (Garrigou et al., 2011), l’utilisation de ces produits et les ressources réelles de protection dans des situations variées (Garrigou et al., 2011 ; Fredj, 2021), ainsi que les perspectives de contributions à la conception des pulvérisateurs (Albert et al., 2021).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".