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Record W7108748087 · doi:10.5281/zenodo.17658050

XRM2024 - Mon05K - "Fragmentation of hunting bullets observed with synchrotron radiation: Lighting up the source of a lesser-known lead exposure pathway"

2024· article· en· W7108748087 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsAmmunitionShot (pellet)ProjectileLead (geology)SynchrotronLead exposureFragmentation (computing)

Abstract

fetched live from OpenAlex

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/

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.020
GPT teacher head0.234
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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