Comparison of the Lactate Pro and the YSI 1500 Sport Blood Lactate Analyzers
Bibliographic record
Abstract
To determine the agreement, reliability, and linearity of the Lactate Pro with the YSI 1500 Sport lactate analyzer, seven male and five female volunteers performed a discontinuous incremental exercise test at discrete percentages of their maximum aerobic power on a cycle ergometer. Five blood samples were collected for each subject; one after each of five increasing workloads. Agreement was evaluated by comparing, in parallel, measurements from the Lactate Pro and the YSI 1500 using Bland-Altman plots. Reliability was determined by performing 10 repeated assays on blood collected at 160 W and 370 W in a randomly selected subject. Strength of association was determined by performing linear regression analysis of the measures obtained from both analyzers. Bland-Altman analysis revealed that blood lactate concentrations from the Lactate Pro were 0.5 ± 1.0 mM (mean ± SD) higher than the YSI 1500 with the limits of agreement being 0.2 to 0.7 mM. Coefficients of variation from blood collected at 80 W and 370 W were 7.1% and 8.9%, respectively. The linear regression equation was Lactate Pro = 1.067(YSI 1500) + 0.036 (R2 = 0.967). In conclusion, the Lactate Pro is reliable and has sufficient agreement and linearity with the YSI 1500 for use in submaximal research and athletic testing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".