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Record W4405396946 · doi:10.1080/1091367x.2024.2440072

Development of Quarter-Mile Walk Tests to Estimate Aerobic Fitness in Children

2024· article· en· W4405396946 on OpenAlexaboutno aff
Matthew T. Mahar, Hoyong Sung

Bibliographic record

VenueMeasurement in Physical Education and Exercise Science · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsnot available
FundersCooper Institute
KeywordsMileQuarter (Canadian coin)Aerobic exerciseStatisticsVO2 maxAerobic capacityMathematicsHeart rateOverweightPhysical fitnessPhysical therapyPsychologyBody mass indexMedicineGeography

Abstract

fetched live from OpenAlex

Field-based tests of aerobic fitness that can be administered quickly and do not require maximal effort are desirable. The purpose was to develop and validate quarter-mile walk tests for 10–13-year-olds. Participants (N = 59) walked one mile on two different days. Walk times, heart rates, body mass, physical activity, and aerobic fitness were assessed. Multiple regression was used to develop models to estimate VO2max. Quarter-mile walk models provided estimates of aerobic fitness that were similar in accuracy to previously published walk tests. The recommended model that balances accuracy and ease of administration was: VO2max = 119.691–(13.744*quarter-mile walk time [min])–(0.168*heart rate), R=.73, SEE = 6.84 mL·kg−1·min−1. Walk times, heart rates, and estimated VO2max values were highly reliable. The walk tests developed provide valid estimates of VO2max, are easy to administer, and could be particularly useful for unmotivated or overweight children when this equation is confirmed with a larger sample in group testing conditions.

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 score0.934
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.326
Teacher spread0.309 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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