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Record W7057717894

Job-Related Aerobic and Musculoskeletal Fitness Standards for Front-Line Structural Firefighters That Qualify as bona fide Occupational Requirements; Critical Considerations

2023· other· en· W7057717894 on OpenAlexaff

Bibliographic record

VenueYork University Digital Library (York University) · 2023
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsYork University
Fundersnot available
KeywordsAerobic exerciseVO2 maxTask (project management)Physical fitnessAerobic capacityProtocol (science)Test (biology)Measure (data warehouse)
DOInot available

Abstract

fetched live from OpenAlex

Maximal oxygen consumption (VO2max) reflects the upper limit of the body’s aerobic fitness and represents the highest rate at which oxygen can be taken up, transported, and utilized by the body. It is the most widely used measure characterizing the effective integration of the body’s many physiological systems in exercise sciences. However, the precise measurement administration protocol and relevance of VO2max regarding physically demanding public safety occupations remain unclear. Structural firefighter applicants routinely have their VO2max measured to ensure that they possess the aerobic fitness required to perform the most frequently occurring and physically demanding on-the-job tasks safely and efficiently. The purpose of this research project was to determine 1) if using a verification phase (VP), following a graded exercise test (GXT), helped to accurately measure VO2max and affected the proportion of participants who met the job-related aerobic fitness standard, 2) if there were any significant relationships between the firefighter applicants’ VO2max, select physical characteristics and simulated job task completion times and performance scores, and 3) what effect short-term reduced-training (i.e., detraining), consequent to the COVID-19 pandemic restrictions, had on the job-related aerobic fitness and critical simulated job task completion times of firefighter applicants. Performing a VP helped to accurately measure VO2max and significantly increased the proportion of participants who met the job-related aerobic fitness standard. A VP should always be used to ensure the measurement of a VO2max and not just a VO2peak. Participants’ VO2max and select physical characteristics had significant negative regression weights on all simulated job task completion times. Multiple regression equations can predict simulated job task completion times and allow applicants to customize their physical activity and exercise regimes to ensure that they have the physical and physiological characteristics to successfully meet the job-related aerobic fitness and simulated job task standards. Short-term periods of reduced training significantly decreased the participants’ ability to meet the job-related aerobic fitness standard. Structural firefighters must engage in habitual exercise regimes to ensure they possess the aerobic and musculoskeletal fitness required to perform critical on-the-job tasks safely and efficiently during emergencies where job completion is critical to safety, life, and property.

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)0.008
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2023
Admission routes1
Has abstractyes

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