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Record W2012248823 · doi:10.1139/h00-017

A Comparison of Critical Velocity Estimates to Actual Velocities in Predicting Simulated Rowing Performance

2000· article· en· W2012248823 on OpenAlexaff
Michael D. Kennedy, Gordon J. Bell

Bibliographic record

VenueCanadian Journal of Applied Physiology · 2000
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRowingMathematicsCritical ionization velocityPower consumptionVO2 maxStatisticsPower (physics)PhysicsMechanicsMedicineThermodynamicsHeart rateInternal medicineGeography

Abstract

fetched live from OpenAlex

The most accurate critical velocity (CV) estimate for the prediction of velocity during a simulated 2,000-m rowing race and the relationship to aerobic power were studied. Sixteen male rowers completed randomized maximal exertion trials (200, 400, 600, 800, 1,000, and 1,200 m), a maximal oxygen consumption (VO(2)max) on a Concept II rowing machine, and an actual 2,000-m simulated rowing race. Three mathematical models were applied to 4 rowing distance combinations producing 12 CV estimates. Seven of the 12 possible CV estimates were not significantly different from actual 2,000-m velocity. Comparison of the 3 CV models using all 6 trial distances revealed that the nonlinear model produced a CV estimate lower than the 2 linear CV models. CV was significantly correlated to VO(2)max (r = 0.91) and the mean velocity achieved during the 2,000-m simulated rowing race (r = 0.97). VO(2)max was significantly correlated to 2,000-m simulated rowing race velocity (r = 0.93).

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.447

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.026
GPT teacher head0.312
Teacher spread0.285 · 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 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

Citations33
Published2000
Admission routes1
Has abstractyes

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