Setting maximum levels for lead in game meat in EC regulations: An adjunct to replacement of lead ammunition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Each year, hunters from 12 of the 27 European Union (EU) countries and the UK shoot over 6 million large game mammals, 12 million rabbits and hares and over 80 million birds. They support an international game meat market worth over 1.1 thousand million Euros. Animals shot with lead ammunition frequently contain lead fragments in the carcass which contaminate meals made from game meat with concentrations of lead substantially above the maximum allowable level (ML) set by European Commission Regulation EC1881/2006 for meat from domesticated animals. This poses a health risk to frequent consumers of wild-shot game meat, with children and pregnant women being particularly vulnerable. Total replacement of lead rifle and shotgun ammunition with available non-toxic alternatives is needed for all hunting in EU nations to prevent exposure of humans and wildlife to ammunition-derived lead and to allow the depletion of the long-term environmental legacy of lead from spent ammunition. We propose that EC1881/2006 is amended to incorporate an ML for game meats as a supplementary measure to the replacement of lead ammunition. This would harmonise food safety standards for lead in meats traded across and imported into the EU.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it