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Record W1991969655 · doi:10.1115/imece2010-39025

Blast Response of Protective Armor Concepts Using an Arm Surrogate

2010· article· en· W1991969655 on OpenAlexaboutno aff
K. E. Simmonds, Amit Bagchi, Peter Matic, Anthony C. Leung, W. M. Pogue, Angus Thompson, J. C. Strain, J. E. Gauvin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsArmourTorsoComputer scienceSurrogate modelReliability engineeringEngineeringAeronauticsRisk analysis (engineering)Medicine

Abstract

fetched live from OpenAlex

Protection and comfort are two key armor requirements to the US warfighter. NRL has supported this effort by developing QuadGard extremity protection [1], and instrumented surrogate torso and brain to assess armor and helmet systems performance [2, 3], among others. Surrogate systems for analyzing personal protection equipment for torso and brain have also been developed by other researchers in US, Australia and Canada and are reported in the literature, but no publications were found on assessment of extremity armors.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.125
GPT teacher head0.517
Teacher spread0.393 · 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.

Study designObservational
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
Published2010
Admission routes1
Has abstractyes

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