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Record W7162487923 · doi:10.14288/hfjc.v19i1.873

What’s Under the Hood? Insight into the Cardiac Function and VO2 Max of an Elite University Distance Runner

2025· article· en· W7162487923 on OpenAlexaffabout
Andrew S. Perrotta

Bibliographic record

VenueOpen Collections · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsCardiorespiratory fitnessStroke volumeVO2 maxAthletesCardiac outputCardiac function curveElite athletesHeart rate

Abstract

fetched live from OpenAlex

Background: Canadian university endurance athletes compete across an extended competitive calendar, requiring them to achieve and maintain high levels of physiological readiness at multiple points throughout the academic year. Purpose: This case study examined seasonal variation in cardiac function and cardiorespiratory performance in an elite female distance runner who competed in both the cross‑country (XC) and indoor track and field (TF) seasons. Methods: Assessments were conducted following each championship period to evaluate peak and submaximal physiological responses using standardized cardiopulmonary exercise testing. Results: Peak cardiorespiratory performance, including VO2Max (mL·kg-1·min-1) and velocity at VO2Max, remained consistent across seasons (XC = 65.9 ‘vs’ TF = 63.8, p = 0.23). Peak stroke volume (mL/beat) was meaningfully higher (MDC95) during TF (TF = 168.0 ‘vs’ XC = 157.8). Max HR (bpm) was significantly reduced during TF (XC = 186 ± 5 ‘vs’ TF =183 ± 3, p < 0.05). Running speed (mph) at ventilatory threshold -2 increased during TF (XC = 9.0 ‘vs’ TF = 9.5). Conclusion: Peak cardiorespiratory performance remained stable across the XC and TF seasons, while running economy and submaximal cardiac function varied considerably. These changes likely reflect seasonal shifts in training volume and intensity tailored to different race demands.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.549
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.007
GPT teacher head0.235
Teacher spread0.229 · 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 designNot applicable
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 routes2
Has abstractyes

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