MétaCan
Menu
Back to cohort
Record W2916664669 · doi:10.1080/23328940.2019.1574200

Finger cold-induced vasodilation test does not predict subsequent cold injuries: A lesson from the 2018 Canadian Forces Exercise

2019· article· en· W2916664669 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTemperature · 2019
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsnot available
Fundersnot available
KeywordsVasodilationTest (biology)MedicinePhysical therapyPhysical medicine and rehabilitationCardiologyGeology

Abstract

fetched live from OpenAlex

A cold-induced vasodilation (CIVD) test was administered to 113 Canadian Armed Forces (CAF) soldiers (age 25.6 ± 6 yrs) during pre-deployment to a Canadian Arctic training exercise. The incidence and rates/types of subsequent peripheral cold injuries, as well as the relationship of CIVD responses against other hypothesized/reported risk factors (smoking, gender, age, ethnicity and prior cold injury), were analyzed. Although there was a wide range of CIVD RIF (resistance index to frostbite) scores (mean = 5.0 ± 1.5), there were no systematic relationships between RIF and injury type/location and rate, and the other risk factors analyzed. The absence of physiological links to cold injury occurrence suggests that in a military cold deployment setting, other factors are in play, which might include clothing, training, leadership and doctrine. These factors should be examined in future work.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.252
Teacher spread0.236 · 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