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Record W3200844994 · doi:10.3138/jmvfh-2021-0051

Chronic pain: The Canadian Armed Forces members and Veterans mental health follow-up survey

2021· article· en· W3200844994 on OpenAlexaffvenueabout
Essence Perera, James M. Thompson, Gordon J. G. Asmundson, Renée El‐Gabalawy, Tracie O. Afifi, Jitender Sareen, Shay‐Lee Bolton

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2021
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsQueen's UniversityUniversity of ReginaUniversity of Manitoba
Fundersnot available
KeywordsChronic painMedicineIrritable bowel syndromePhysical therapyPopulationMilitary personnelPain catastrophizingMental healthPsychiatry

Abstract

fetched live from OpenAlex

LAY SUMMARY Chronic pain is pain that has lasted three to six months or longer. Many people with back pain, migraines, arthritis, and gastrointestinal conditions such as irritable bowel syndrome, have chronic pain. The experience of chronic pain may have various negative effects on individuals. Pain may prevent a person from doing everyday tasks such as household chores. Chronic pain is an understudied area of research among military members and Veterans. Thus, the authors explored chronic pain in the Canadian military population. This study looked at the differences in chronic pain conditions among serving personnel and Veterans. The results show that a majority of serving members and Veterans experience chronic pain conditions. Veterans also reported experiencing more chronic pain than serving members.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.027
GPT teacher head0.304
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations12
Published2021
Admission routes3
Has abstractyes

Explore more

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