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Record W2057423744 · doi:10.1139/h10-053

Perceived exertion and heart rate models for estimating metabolic workload in elite British soldiers performing a backpack load-carriage task

2010· article· en· W2057423744 on OpenAlexvenueno aff
Richard J. Simpson, Scott M. Graham, Geraint Florida‐James, Christopher Connaboy, Richard Clement, Andrew S. Jackson

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2010
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsnot available
FundersCarnegie Trust for the Universities of Scotland
KeywordsBackpackWorkloadHeart rateRating of perceived exertionMedicinePhysical therapySimulationPhysical medicine and rehabilitationComputer scienceInternal medicineBlood pressureEngineering

Abstract

fetched live from OpenAlex

Identifying field measures to estimate backpack load-carriage work intensity in elite soldiers is of interest to the military. This study developed rating of perceived exertion (RPE) and heart rate models to define metabolic workload for a backpack load-carriage task valid for a population of elite soldiers using serial data. Male soldiers (n = 18) from the British Parachute or Special Air Service Regiment completed an incremental treadmill walking and (or) running protocol while carrying a 20-kg backpack. Heart rate, RPE, and oxygen uptake were recorded at each incremental stage of the protocol. Linear mixed models were used to model the RPE and heart rate data in the metric of measured peak oxygen uptake. Workload was accurately estimated using RPE alone (SE = 6.03), percentage of estimated maximum heart rate (%E-MHR) (SE = 6.9), and percentage of measured maximum heart rate (%M-MHR) (SE = 4.9). Combining RPE and %E-MHR resulted in a field measure with an accuracy (SE = 4.9) equivalent to the %M-MHR model. We conclude that RPE, %E-MHR, and %M-MHR provide accurate field-based proxy measures of metabolic workload in elite British soldiers performing a backpack load-carriage task. The model is accurate for the metabolic range measured by these serial data for the backpack load-carriage task.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.347
Teacher spread0.317 · 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.

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

Citations15
Published2010
Admission routes1
Has abstractyes

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