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Record W2031019767 · doi:10.1139/h03-044

Effects of Different Stepwise Reduction Taper Protocols on Cycling Performance

2003· article· en· W2031019767 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2003
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsTaperingCardiorespiratory fitnessTime trialCyclingVolume (thermodynamics)Reduction (mathematics)Intensity (physics)MedicineTraining (meteorology)MathematicsPhysical therapyAnimal scienceSimulationComputer scienceInternal medicineBiologyPhysicsHeart rateOptics

Abstract

fetched live from OpenAlex

This study examined the effects of different 7-day taper protocols on simulated 20-km time trials (20TT). Following 3 weeks of baseline training, 11 male cyclists (.VO2max = 4.78 +/- 0.66 L.min-1) were randomly assigned to one of three stepwise reduction tapers in which training volume was reduced by 30% (T30, n = 5), 50% (T50, n = 6), or 80% (T80, n = 6) of baseline training with intensity (85% .VO2max) maintained. Cardiorespiratory measurements were collected every 5 km during the 20TT. Results revealed a significant (5.4%, 0.05) improvement in 20TT performance in the T50 protocol with concomitant increases in .VO2 and O2 pulse. No significant differences were found in T30 or T80. These results showed that a moderate (50%) reduction in weekly training volume appeared to be optimal in terms of enhancing performance. This confirms the contention that proper placement of training volume during tapering, while maintaining exercise intensity, can elicit performance improvements.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.471
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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