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Record W4413436133 · doi:10.1016/j.envpol.2025.127010

Inaccurate and misleading terminology may impede the protection of people and wildlife from adverse effects of lead ammunition

2025· article· en· W4413436133 on OpenAlexaff
Vernon G. Thomas, Rhys E. Green, Deborah J. Pain

Bibliographic record

VenueEnvironmental Pollution · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAmmunitionWildlifeTerminologyLead (geology)Environmental scienceEnvironmental planningEnvironmental healthEnvironmental protectionMedicineEcologyGeographyBiologyArchaeology

Abstract

fetched live from OpenAlex

Inaccurate terminology and misinformation about lead (Pb) ammunition's toxicity may obstruct proposed regulation requiring use of non-lead substitutes. Elemental lead of anthropogenic origin in the environment is often confused with naturally-occurring lead ore compounds in the scientific literature, leading to suggestions that its use cannot be regulated. Inaccurate and misleading statements about the composition of substitutes for lead ammunition and fishing weights can cause public misunderstanding about their use and hinder proposals to end the use of lead-based products. It is necessary to clarify the composition of lead substitutes in nationally/internationally-approved lists of non-toxic products and to make them publicly available. Suitable products already exist but need to be adopted in most countries' legislation, especially if a broad transition to lead substitutes for all hunting ammunition and fishing weights is to be adopted. These concerns apply especially to the European Union, the United Kingdom, and other countries in which much scientific evidence supports the use of non-lead substitutes.

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 imitation

Not 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.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0040.012
Scholarly communication0.0060.007
Open science0.0030.005
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0080.008

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

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