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Record W3044573348 · doi:10.1007/s00414-020-02378-x

Ballistic protective properties of material representative of English civil war buff-coats and clothing

2020· article· en· W3044573348 on OpenAlexfundno aff
B. A. May, Richard Critchley, D. J. Carr, Alan Peare, Keith Dowen

Bibliographic record

VenueInternational Journal of Legal Medicine · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsnot available
FundersMinistère de la Défense NationaleCranfield University
KeywordsClothingProjectileMuzzleShot (pellet)AeronauticsBallisticsEngineeringForensic engineeringLawPhysicsMaterials scienceMechanical engineeringPolitical science

Abstract

fetched live from OpenAlex

One type of clothing system used in the English Civil War, more common amongst cavalrymen than infantrymen, was the linen shirt, wool waistcoat and buff-coat. Ballistic testing was conducted to estimate the velocity at which 50% of 12-bore lead spherical projectiles ( V 50 ) would be expected to perforate this clothing system when mounted on gelatine (a tissue simulant used in wound ballistic studies). An estimated six-shot V 50 for the clothing system was calculated as 102 m/s. The distance at which the projectile would have decelerated from the muzzle of the weapon to this velocity in free flight was triple the recognised effective range of weapons of the era suggesting that the clothing system would provide limited protection for the wearer. The estimated V 50 was also compared with recorded bounce-and-roll data; this suggested that the clothing system could provide some protection to the wearer from ricochets. Finally, potential wounding behind the clothing system was investigated; the results compared favourably with seventeenth century medical writings.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.472

Codex and Gemma teacher scores by category

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

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 head0.084
GPT teacher head0.421
Teacher spread0.337 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2020
Admission routes1
Has abstractyes

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