Standardization of reticulocyte counts in the athlete biological passport: A practical update
Bibliographic record
Abstract
INTRODUCTION: The athlete biological passport monitors blood variables over time to uncover blood doping. With the phasing in of a new series of blood analyzers, the Sysmex XN series, it was necessary to examine the comparability of results with the previously employed XT/XE series. A previous comparison between XN and XT/XE series suggested a small but significant bias between the two instruments in the measurements of RET%. Here, we examined the comparability of RET% on the XN and XT/XE platform using data collected over the first year since the transition. METHODS: The comparability of results obtained from XN and XT/XE instruments was assessed using three datasets: (i) 767 blood samples measured on both instrument series in 22 WADA-accredited laboratories, (ii) 27 323 samples measured on either instrument across 31 laboratories, and (iii) 119 clinical samples and 110 anti-doping samples measured on both instruments in a single laboratory. RESULTS: Analysis of the three datasets confirms the previous observation of a bias toward higher RET% values for samples measured on Sysmex XN instruments compared with the XT/XE series. Using data across a larger number of XN instruments and a larger athlete population, the current work suggests that the bias is proportional and slightly higher than previously observed across most of the range RET% values. CONCLUSION: A model is proposed for the comparison of data across XN and XT/XE technologies whereby the instrument bias increases proportionally with RET% measured on Sysmex XN Series, but where the rate of increase is negatively related to IRF%.
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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 | 0.000 | 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".