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Record W4311887338 · doi:10.3138/jmvfh-2021-0114

Putting your best weighted foot forward: Reviewing lower extremity injuries by sex in weighted military marching

2022· article· en· W4311887338 on OpenAlexaffvenueabout
Jacinta McNairn, Justin Tait, Madeline Harlow, Peter Yang, Brian Beaudette, Paul Dhillon

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsQueen's UniversityDalhousie UniversityNOSM UniversityCanadian Armed Forces
Fundersnot available
KeywordsAnthropometryFoot (prosody)DelegationCarriageMedicinePhysical therapyPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

LAY SUMMARY International marching events, such as the Nijmegen Marches, have a prominent place in Canadian military history, and participation continues today. In the Dutch military, the load carriage requirements previously differed by sex, with men carrying 10 kilograms during the march and women carrying no weight. The Canadian delegation requires both male and female participants to carry 10 kilograms. This article examines the effect of this policy on possible injuries using a Gender-based Analysis Plus lens. Weight carriage should focus on anthropometric factors, not sex, which will allow for appropriate and equal increased stresses (weight) for march participants while minimizing injuries.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.058
GPT teacher head0.390
Teacher spread0.332 · 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
Published2022
Admission routes3
Has abstractyes

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