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Record W7038536098

INJURY RISK TO THE UPPER EXTREMITY RESULTING FROM BEHIND SHIELD BLUNT TRAUMA

2023· dissertation· en· W7038536098 on OpenAlexfundno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicHomicide, Infanticide, and Child Abuse
Canadian institutionsnot available
FundersMcMaster University
KeywordsProjectileShieldsShieldStiffnessFace shieldFracture (geology)Poison controlDeformation (meteorology)Instrumentation (computer programming)
DOInot available

Abstract

fetched live from OpenAlex

Ballistic shields are supported by a user’s arm, placing the upper extremity at close proximity to the back-face of the shield. Although ballistic shields must pass a protective standard that outlines projectile (bullet) penetration; there is no standard that stipulates the amount of acceptable deformation when ballistic shields stop or deflect projectiles. There are no injury criteria developed for the high-rate, short duration and focal loading that is typical of shield back-face deformation from these events. In this research, an anthropomorphic test device (ATD) was modified to allow for additional instrumentation capable of measuring these loads. It was then used in a ballistic testing facility to quantify loading at the hand, wrist, forearm, and elbow. A lightweight projectile was created that matched the shape and stiffness of the deforming ballistic shield and impacts within 5% of the peak force measured in the ballistic testing facility were applied with it to post-mortem human subjects (PMHS) until failure. Eight 50th percentile male PMHS pairs were segmented at the mid-humerus and impacted to failure to determine the fracture threshold of the hand, wrist, forearm, and elbow, confirmed by x-ray imaging. The peak force required to generate fracture varied significantly among anatomical location, indicating boundary conditions influence failure threshold. Further, these injury criteria were substantially different than previously reported criteria for other loading events (e.g., automotive), highlighting the importance of developing injury criteria specific for the intended application. An existing finite element human body model designed for automotive impacts was also assessed for its applicability to predict injury in these high-rate loading scenarios, and performed well for peak force, but not for the force-time curve shape. This is the first study of its kind to assess injury risk resulting from shield behind armour blunt trauma, and results from this work will inform a protective standard to assess ballistic shields.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.718
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.001

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 head0.016
GPT teacher head0.251
Teacher spread0.235 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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