The effect of pre-test carbohydrate ingestion on the anaerobic threshold, as determined by the lactate-minimum test
Bibliographic record
Abstract
The purpose of this study was to investigate the effect of pre-test carbohydrate (CHO) ingestion on anaerobic-threshold assessment using the lactate-minimum test (LMT). Fifteen competitive male distance runners capable of running 10 km in 33.5-43 min were used as subjects. LMT was performed following CHO (2x300 mL, 7% solution) or comparable placebo (Pl) ingestion, in a double-blind, randomized order. The LMT consisted of two high-intensity 1 min treadmill runs (17-21 km.h(-1)), followed by an 8 min recovery period. Subsequently, subjects performed 5 min running stages, incremented by 0.6 km.h(-1) and separated by 1 min blood-sampling intervals. Tests were terminated after 3 consecutive increases in blood-lactate concentration ([La]) had been observed. Finger-tip capillary blood was sampled for [La] and blood-glucose determination 30 min before the test's onset, during the recovery phase following the 2 high-intensity runs, and following each of the subsequent 5 min stages. Heart rate (HR) and rating of perceived exertion (RPE) were recorded after each stage. The lactate-minimum speed (LMS) was determined from the individual [La]-velocity plots and was considered reflective of the anaerobic threshold. Pre-test CHO ingestion had no effect on LMS (13.19+/-1.12 km.h(-1) vs. 13.17+/-1.08 km.h(-1) in CHO and Pl, respectively), nor on [La] and glucose concentration at that speed, or on HR and RPE responses. Pre-test CHO ingestion therefore does not affect LMS or the LMT-estimated anaerobic threshold.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".