XRM2024 - Mon05K - "Fragmentation of hunting bullets observed with synchrotron radiation: Lighting up the source of a lesser-known lead exposure pathway"
Bibliographic record
Abstract
Abstract: The majority of hunters use firearms to hunt wild game, and traditional hunting ammunition contains lead, sometimes exclusively. When a lead projectile passes through an animal, it leaves behind a trail of tiny lead fragments which can extend well beyond the projectile path. These fragments are too small to be sensed while eating, and become a lead exposure pathway: They end up being consumed by humans who eat the meat, and also scavengers that eat the butchered remains that are returned to the landscape. The harmful effects of ingesting lead bullet fragments or lead shot have been reported for more than 100 species of wildlife worldwide. Bullet fragments embedded in game meat have been revealed using medical radiography in previous studies. We have recently applied synchrotron X-ray imaging to ammunition fragmentation for the first time. Our first report [1,2] used the BMIT beamline of the Canadian Light Source, which allowed us to image and resolve tens of thousands of fragments in the sub-10 µm size range where they were not previously known to exist, 20× smaller than what has been revealed with medical radiography. K edge subtraction (KES) imaging was also applied to confirm the elemental composition of the fragments in-situ. We have since extended our studies into the sub-micron size regime using scanning X-ray nanoprobes, and to other types of ammunition and tissues. The results challenge the current understanding of the maximum extent that fragments may be distributed, and the effectiveness of imaging methods used to screen wild game donations at food banks for lead bullet fragments. References:[1] Leontowich, A. F. G., Panahifar, A., Ostrowski, R. (2022) "Fragmentation of hunting bullets observed with synchrotron radiation: Lighting up the source of a lesser-known lead exposure pathway" PLoS ONE, 17(8) e0271987 [2] https://www.cheminst.ca/magazine/article/synchrotron-imaging-reveals-size-and-spread-of-lead-bullet-fragments-in-wild-game/
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".