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Record W2133340703 · doi:10.1123/pes.18.3.364

Secular Changes in Shuttle-Run Performance: A 23-Year Retrospective Comparison of 9- to 11-Year-Old Children

2006· article· en· W2133340703 on OpenAlexaboutno aff
Katharine E. Reed, Darren E. R. Warburton, Crystal Whitney, Heather McKay

Bibliographic record

VenuePediatric Exercise Science · 2006
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
Fundersnot available
KeywordsPercentileCohortMulti-stage fitness testMedicineDemographyAerobic exercisePhysical fitnessIncidence (geometry)Fitness testRetrospective cohort studyCohort studyGerontologyPediatricsPhysical therapyStatisticsMathematicsInternal medicine

Abstract

fetched live from OpenAlex

Low physical fitness is associated with increased risk of cardiovascular disease (CVD) in adults and a higher incidence of CVD risk factors in children. Our aim was to compare the aerobic performance of Canadian children in 2004 with that of children measured 2 decades ago. We conducted a cross-sectional comparison of 2 data sets: (a) a 2004 cohort (n = 252) and (b) data from Leger’s 1981 cohort (n = 2,151). Performance was assessed using Leger’s 20 m Shuttle Run Test. First, we compared VO2max by cohort (in age and sex subgroups). Second, we used 1981 derived data, to re-create the original distribution curves, then calculated a 1981 equivalent percentile for each 2004 cohort child. We found that aerobic performance was lower at all ages in 2004 compared with 1981 (p < .01). Thus, the 50th percentile for fitness of children in 2004 was equivalent to that of children in the lowest 20% of fitness in 1981. We support the view that the performance of children on aerobic fitness tests is declining.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.960

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.008
GPT teacher head0.261
Teacher spread0.253 · 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 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

Citations9
Published2006
Admission routes1
Has abstractyes

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