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Record W1978375089 · doi:10.1002/ajhb.10084

Secular trend in peak oxygen consumption among United States youth in the 20th century

2002· article· en· W1978375089 on OpenAlexaff
Joey C. Eisenmann, Robert M. Malina

Bibliographic record

VenueAmerican Journal of Human Biology · 2002
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsYork University
Fundersnot available
KeywordsSecular variationDemographyPopulationBody mass indexMedicineSociologyInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this study was to examine secular change in peak oxygen consumption (Vo(2)) in U.S. boys and girls using available data from the 20th century. Studies were primarily identified from review articles and a Medline search. To be included in the analysis, studies must have included direct measurement of peak Vo(2) on healthy (free from overt disease) United States children and youth from the general population separated by sex. Data (mean values) were divided by decade and separated into three age groups: 6-12, 13-15, and 16-18 years for boys, and 6-11, 12-14, and 15-18 years for girls. Peak Vo(2) values were expressed as related to bipedal locomotion; therefore, cycle ergometry values were corrected by a factor of 1.075. Mean values were fit by least squares, goodness-of-fit regression lines. Results indicate that absolute (L x min(-1)) and relative (ml x kg(-1) x min(-1)) peak Vo(2) have remained relatively stable among boys and young girls. In adolescent girls, particularly those 15 years of age and older, peak Vo(2) has decreased by approximately 20% over the past few decades. The available data indicate that aerobic fitness has not decreased in United States youth except in adolescent girls over the past few decades.

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)0.002
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.027
GPT teacher head0.284
Teacher spread0.257 · 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

Citations58
Published2002
Admission routes1
Has abstractyes

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