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Record W1995065060 · doi:10.3357/amhp.4027.2015

Night Vision Goggle-Induced Neck Pain in Military Helicopter Aircrew: A Literature Review

2014· review· en· W1995065060 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAerospace Medicine and Human Performance · 2014
Typereview
Languageen
FieldMedicine
TopicOcular and Laser Science Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsAircrewAviation medicineMedicineNight visionNeck painAeronauticsSpace medicineMilitary personnelPhysical medicine and rehabilitationEngineeringComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Neck pain occurs at a significant rate in the military helicopter community. It is often attributed to the use of night vision goggles (NVG) and to a number of additional factors such as anthropometrics, posture, vibration, mission length, physical fitness, and helmet fit or load. A number of research studies have addressed many aspects of this epidemic, but an up-to-date and comprehensive review of the literature is not currently available. This paper reviews the spinal anatomy in general and then summarizes what is known about the incidence and prevalence of neck injuries, how the operational environments and equipment may contribute to these injuries, and what can be done to address them from a prevention and/or rehabilitation perspective. Harrison MF, Coffey B, Albert WJ, Fischer SL. Night vision goggle-induced neck pain in military helicopter aircrew: a literature review.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.038
GPT teacher head0.387
Teacher spread0.349 · 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