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Record W7112927119

Military Forensic Medicine

2025· article· en· W7112927119 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Southern Denmark Research Portal (University of Southern Denmark) · 2025
Typearticle
Languageen
FieldMedicine
TopicTraumatic Ocular and Foreign Body Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsStandardizationDeliverableRisk assessmentMilitary personnel
DOInot available

Abstract

fetched live from OpenAlex

In 2010 NATO decided to form a Team of Experts to look into non-lethal weapons, and a subgroup og this was non-lethal kinetic energy weapons. The group was called the Non-Lethal Kinetic Energy Team of Experts (NLKE ToE) under the aegis of the NATO Army Armaments Group Joint Non-Lethal Weapons Capability Group (NAAG JNLW CG). The object of the group was to define common test procedures for the various participating laboratories in the domain of blunt trauma effects. A general Standardization Recommendation (STANREC) called “Risk assessment of non-lethal kinetic energy projectiles” (STANREC 4744) was developed. The defined deliverable for the ToE were Allied Engineering Papers (AEP) in the shape of propositions of standardization in the following areas: Skin Penetration AEP-94 was called “Skin Penetration Assessment of Non-Lethal Projectiles”; Accuracy AEP-98 “Precision assessment of non-lethal kinetic energy weapons and ammunition”; Chest impact AEP 99 “Thorax injury risk assessment of non-lethal projectiles” and Head impact AEP-103 “Head injuries assessment of non-lethal projectiles”. Abdominal impact and Effectiveness are currently both being produced. Members of the ToE are technical experts in different fields and currently one forensic pathologist. The ToE meets biannually in the participating nations, and the nations are Belgium (Chair and secretariat at the Royal Military Academy, Brussels), Canada, Denmark, France, Germany, the Netherlands, Sweden, Switzerland, the UK, and the USA.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.026
GPT teacher head0.275
Teacher spread0.248 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

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