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Record W4391227509 · doi:10.1186/s40779-024-00509-8

Nickel’s carcinogenicity: the need of more studies to progress

2024· letter· en· W4391227509 on OpenAlexaff
Consolato Sergi

Bibliographic record

VenueMilitary Medical Research · 2024
Typeletter
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsChildren's Hospital of Eastern OntarioStollery Children's HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineCarcinogenNickelMetallurgyBiochemistry

Abstract

fetched live from OpenAlex

On March 8-15, 2022, a board of international scientists assembled in Lyon to evaluate the carcinogenicity of cobalt metal, cobalt(II) salts, antimony trioxide, and weapons-grade tungsten alloy harboring nickel and cobalt [1].The 131st International Agency for Research on Cancer (IARC) Monograph is the result of a 6-9month work of perusing the literature, slide evaluation, data interpretation, and interim meetings.The assessment of cobalt, antimony, and nickel-containing alloys will have tremendous consequences for the industry, health, and defense departments [1].Armor-penetrating projectiles utilize tungsten alloys of weapons-grade quality, consisting of 91-93% tungsten, 2-4% cobalt, and 3-5% nickel.Inhalation of hazardous substances can occur because of occupational exposure in weapons production.Both military personnel and civilians may encounter nickel-containing metal aerosols that are generated during the firing or impact of weapons.Long-term exposure to residual embedded fragments from munitions can pose significant hazards.The available exposure data were limited, nevertheless, the

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)0.009
metaresearch head score (Gemma)0.021
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.035
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0050.008
Open science0.0020.002
Research integrity0.0350.038
Insufficient payload (model declined to judge)0.0070.007

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 head0.082
GPT teacher head0.410
Teacher spread0.328 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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