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Record W2134091681 · doi:10.1139/h02-014

The Lactate Minimum Test for Cycling: Estimation of the Maximal Lactate Steady State

2002· article· en· W2134091681 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 · 2002
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBlood lactateAnaerobic exerciseSprintLactic acidLactate thresholdEndurance trainingSteady state (chemistry)Animal scienceChemistryMedicineInternal medicinePhysical therapyHeart rateBiology

Abstract

fetched live from OpenAlex

This study evaluated the reliability and validity of the lactate minimum test (LMT), an incremental test given after lactic acidosis was induced by sprint exercise. This test is purported to accurately estimate the intensity of exercise at which the transport of lactate into and out of the blood is in equilibrium (maximal lactate steady state or MLSS) and should be a good predictor of endurance performance. Fourteen athletes (mean age 27.2 +/- 3.7 yrs) completed the following on Kreitler rollers: (a) two 20-km time-trials (35.1 +/- 3.3 and 35.7 +/- 3.5 km.hr-1, p < .05); (b) two LMTs yielding lactate minimum speeds (LMS) of 33.6 +/- 3.4 and 33.4 +/- 3.1 km.hr-1 (p > 0.6); and (c) four constant intensity rides, at speeds bracketing the LMS. At 33.5 +/- 3.1 km.hr-1 plasma lactate concentration decreased 0.4 +/- 1.6 mM from 10 to 30 min. Plasma lactate increased 1.6 +/- 0.7 mM while riding 0.9 +/- 0.9 km.hr-1 faster. The LMT is a reliable (r2 = 0.904) and valid method to predict MLSS and a good predictor of endurance performance (LMT vs. 20-km time-trial, r2 = 0.86).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.235

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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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