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Record W4413813129 · doi:10.1101/2025.08.27.25334536

Determination of maximal oxygen uptake in adolescents

2025· preprint· en· W4413813129 on OpenAlexaff
Petri Jalanko, Emilia Laitinen, Dimitris Vlachopoulos, Ying Gao, Alan R. Barker, Bert Bond, Earric Lee, Eero A. Haapala

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsOxygenVO2 maxEnvironmental scienceChemistryInternal medicineMedicine

Abstract

fetched live from OpenAlex

Abstract Purpose An oxygen uptake ( V̇O 2 ) plateau, despite an increased work rate, is considered the gold standard for confirming if exercise test performance reflects maximal oxygen uptake (V̇O 2max ). We investigated whether adolescents demonstrate a V̇O 2 plateau during an incremental test or if a supramaximal verification phase is necessary to confirm V̇O 2max . We also investigated the impact of using moving versus binned time averages on V̇O 2max values, and how these processing strategies influence the interpretation of the verification phase in confirming V̇O 2max . Methods A total of 27 adolescents (16 girls) aged 12 to 14 years completed an incremental cycle ergometer ramp test to exhaustion. After a 15-minute recovery, a verification phase was conducted at 105% of their incremental test peak power. V̇O 2max was analysed using 15-second binned and moving averages. Results Out of 27 participants, 5 (19%) demonstrated a plateau in V̇O 2 during an incremental test. V̇O 2max was confirmed in the verification phase for 23 out of the 27 adolescents (85%). The moving V̇O 2max (mL/kg/min) averages were higher than the binned V̇O 2 values in the incremental test (1.8%) and the verification phase (2.4%) (P<0.0001). Processing strategies did not affect the confirmation of V̇O 2max . Conclusion A verification phase is necessary for accurately determining V̇O 2max in adolescents, who often do not reach a V̇O 2 plateau. The processing strategies of exercise tests should be reported, as different strategies can lead to variations in V̇O 2max results. However, these processing strategies do not impact the utility of the verification test.

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)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.283
Teacher spread0.264 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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