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Record W3122713864 · doi:10.3138/jmvfh-2019-0063

Quantifying physiological responses during simulated tasks among Canadian firefighters: A systematic review and meta-analysis

2021· review· en· W3122713864 on OpenAlexaffvenueabout
Goris Nazari, Steve Lu, Joy C. MacDermid

Bibliographic record

VenueJournal of Military Veteran and Family Health · 2021
Typereview
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsMcMaster UniversityWestern University
Fundersnot available
KeywordsFirefightingExertionWork (physics)Set (abstract data type)Meta-analysisPhysical fitnessComputer sciencePerceived exertionApplied psychologyRisk analysis (engineering)MedicinePsychologyPhysical therapyEngineeringHeart rateBlood pressure

Abstract

fetched live from OpenAlex

LAY SUMMARY Firefighting involves a high level of physical exertion with tremendous demands on the heart and body. It is necessary to quantify levels of physical work exertion in firefighting to set physical fitness standards firefighters need to meet to improve performance, efficiency, and possibly decrease injury risks. Researchers need to focus on and develop exercise programs that are specific to firefighters so that they can be prepared and able to do their work safely.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.514
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0110.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.393
GPT teacher head0.512
Teacher spread0.118 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations16
Published2021
Admission routes3
Has abstractyes

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