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Record W2806903475 · doi:10.1123/ijspp.2018-0100

The Reliability of 4-Minute and 20-Minute Time Trials and Their Relationships to Functional Threshold Power in Trained Cyclists

2018· article· en· W2806903475 on OpenAlexaff
Martin J. MacInnis, Aaron C. Q. Thomas, Stuart M. Phillips

Bibliographic record

VenueInternational Journal of Sports Physiology and Performance · 2018
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIntraclass correlationReliability (semiconductor)MedicineAnimal scienceCyclingLimits of agreementMathematicsStatisticsPhysical therapyReproducibilityNuclear medicinePower (physics)BiologyPhysics

Abstract

fetched live from OpenAlex

PURPOSE: The mean power output (MPO) from a 60-min time trial (TT)-also known as functional threshold power, or FTP-is a standard measure of cycling performance; however, shorter performance tests are desirable to reduce the burden of performance testing. The authors sought to determine the reliability of 4- and 20-min TTs and the extent to which these short TTs were associated with 60-min MPO. METHODS: Trained male cyclists (n = 8; age = 25 [5] y; VO2max = 71 [5] mL/kg/min) performed two 4-min TTs, two 20-min TTs, and one 60-min TT. Critical power (CP) was estimated from 4- and 20-min TTs. The typical error of the mean (TEM) and intraclass correlation coefficient (ICC) were calculated to assess reliability, and R2 values were calculated to assess relationships with 60-min MPO. RESULTS: Pairs of 4-min TTs (mean: 417 [SD: 45] W vs 412 [49] W, P = .25; TEM = 8.1 W; ICC = .98), 20-min TTs (342 [36] W vs 344 [33] W, P = .41; TEM = 4.6 W; ICC = .99), and CP estimates (323 [35] W vs 328 [32] W, P = .25; TEM = 6.5; ICC = .98) were reliable. The 4-min MPO (R2 = .95), 20-min MPO (R2 = .92), estimated CP (R2 = .82), and combination of the 4- and 20-min MPO (adjusted R2 = .98) were strongly associated with the 60-min MPO (309 [26] W). CONCLUSION: The 4- and 20-min TTs appear useful for assessing performance in trained, if not elite, cyclists.

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)0.002
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 score0.029
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.036
GPT teacher head0.293
Teacher spread0.257 · 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

Citations46
Published2018
Admission routes1
Has abstractyes

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