MétaCan
Menu
Back to cohort
Record W4405071404 · doi:10.1007/s00421-024-05674-1

Exercise training-induced speeding of $${\dot{\text{V}}\text{O}}_{{2}}$$ kinetics is not intensity domain-specific or correlated with indices of exercise performance

2024· article· en· W4405071404 on OpenAlexafffund
Erin Calaine Inglis, Letizia Rasica, Danilo Iannetta, Kate M. Sales, Daniel A. Keir, Martin J. MacInnis, Juan M. Murias

Bibliographic record

VenueEuropean Journal of Applied Physiology · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsWestern UniversityUniversity of Calgary
FundersKillam TrustsHamad Bin Khalifa UniversityNatural Sciences and Engineering Research Council of CanadaQatar National LibraryHeart and Stroke Foundation of Canada
KeywordsIntensity (physics)AlgorithmSprintArtificial intelligenceMachine learningComputer sciencePhysicsMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Abstract Purpose This study examined the effect of 3 and 6 weeks of intensity domain-based exercise training on $${\dot{\text{V}}\text{O}}_{{2}}$$ V ˙ O 2 kinetics changes and their relationship with indices of performance. Methods Eighty-four young healthy participants (42 M, 42 F) were randomly assigned to six groups (14 participants each, age and sex-matched) consisting of: continuous cycling in the (1) moderate (MOD)-, (2) lower heavy (HVY1)-, and (3) upper heavy-intensity (HVY2)- domain; interval cycling in the (4) severe-intensity domain (i.e., high-intensity interval training (HIIT), or (5) extreme-intensity domain (i.e., sprint-interval training (SIT)); or (6) control (CON). Training participants completed two three-week phases of three supervised sessions per week, with physiological evaluations performed at PRE, MID and POST intervention. All training protocols, except SIT, were work-matched. Results There was a significant time effect for the time constant ( $$\tau {\dot{\text{V}}\text{O}}_{{2}}$$ τ V ˙ O 2 ) between PRE (31.6 ± 10.4 s) and MID (22.6 ± 6.9 s) (p < 0.05) and PRE and POST (21.8 ± 6.3 s) (p < 0.05), but no difference between MID and POST (p > 0.05) and no group or interaction effects (p > 0.05). There were no PRE to POST differences for CON (p < 0.05) in any variables. Despite significant increases in maximal $${\dot{\text{V}}\text{O}}_{{2}}$$ V ˙ O 2 ( $${\dot{\text{V}}\text{O}}_{{{\text{2max}}}}$$ V ˙ O 2max ), estimated lactate threshold (θLT), maximal metabolic steady state (MMSS), and peak power output (PPO) for the intervention groups (p < 0.05), there were no significant correlations from PRE to MID or MID to POST between $$\Delta \tau {\dot{\text{V}}\text{O}}_{{2}}$$ Δ τ V ˙ O 2 and $$\Delta {\dot{\text{V}}\text{O}}_{{{\text{2max}}}}$$ Δ V ˙ O 2max (r = – 0.221, r = 0.119), ΔPPO (r = – 0.112, r = – 0.017), ΔθLT (r = 0.083, r = 0.142) and ΔMMSS (r = – 0.213, r = 0.049)(p > 0.05). Conclusion This study demonstrated that (i) the rapid speeding of $${\dot{\text{V}}\text{O}}_{{2}}$$ V ˙ O 2 kinetics was not intensity-dependent; and (ii) changes in indices of performance were not significantly correlated with $$\Delta \tau {\dot{\text{V}}\text{O}}_{{2}}$$ Δ τ V ˙ O 2 .

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0040.000

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 head0.031
GPT teacher head0.240
Teacher spread0.209 · 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

Citations2
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Journal of Applied PhysiologySame topicCardiovascular and exercise physiologyFrench-language works237,207