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Record W1990208371 · doi:10.1080/15438620009512563

Critical aerobic power during simulated 20 km bicycle racing

2000· article· en· W1990208371 on OpenAlexaff
Michael K. Stickland, Stewart R. Petersen, Rudolph H. Dressendorfer

Bibliographic record

VenueSports medicine, training, and rehabilitation/Sports medicine, training and rehabilitation · 2000
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCyclingVO2 maxTime trialAnimal scienceLactate thresholdBlood lactateMathematicsHeart rateMedicineInternal medicineBiology

Abstract

fetched live from OpenAlex

The main purpose of the study was to investigate the relationships between the Lactate Threshold (LT), maximal oxygen uptake (KO2max), performance time, and Critical Aerobic Power (CAP) during a simulated 20 km cycling time trial (20 kmTT). CAP was operationally defined as the average oxygen uptake sustained during the 20 kmTT. The subjects were 11 experienced male cyclists (mean±SD age: 29±7.2 yr; VO2max: 4.51±0.11 (L · min−1). Each subject completed two 20 kmTT using their own racing bicycle on a custom designed, computerized roller system. Elapsed time for the best trial averaged 34.58 ±3.29 min. Test‐retest reliability estimates for elapsed time, average heart rate and VO2 during the two trials were 0.92, 0.98 and 0.98, respectively. Oxygen uptake during the 20 kmTT averaged 115% of VO2 at LT and 86% of FO2max· A significant correlation was found between CAP and performance time (r= —0.81, p ≤ 0.01). Significant correlations were found between CAP and VO2 at LT (r = 0.62, p ≤ 0.05) and CAP and VO2max (r = 0.97, p ≤ 0.05). Using stepwise regression, VO2max was the strongest predictor of CAP with no further contribution from VO2 at LT. It was concluded that CAP is a strong determinant of cycling performance for 30–40 min duration. In this study, CAP was dependent more on VO2max than on the LT.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.275
Teacher spread0.266 · 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.

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

Citations10
Published2000
Admission routes1
Has abstractyes

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