Validation of a blood marker for plasma volume in endurance athletes during a live‐high train‐low altitude training camp
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.
Bibliographic record
Abstract
Abstract Altitude is a confounding factor within the Athlete Biological Passport (ABP) due, in part, to the plasma volume (PV) response to hypoxia. Here, a newly developed PV blood test is applied to assess the possible efficacy of reducing the influence of PV on the volumetric ABP markers; haemoglobin concentration ([Hb]) and the OFF‐score. Endurance athletes (n=34) completed a 21‐night simulated live‐high train‐low (LHTL) protocol (14 h.d ‐1 at 3000 m). Bloods were collected twice pre‐altitude; at days 3, 8, and 15 at altitude; and 1, 7, 21, and 42 days post‐altitude. A full blood count was performed on the whole blood sample. Serum was analysed for transferrin, albumin, calcium, creatinine, total protein, and low‐density lipoprotein. The PV blood test (consisting of the serum markers, [Hb] and platelets) was applied to the ABP adaptive model and new reference predictions were calculated for [Hb] and the OFF‐score, thereby reducing the PV variance component. The PV correction refined the ABP reference predictions. The number of atypical passport findings (ATPFs) for [Hb] was reduced from 7 of 5 subjects to 6 of 3 subjects. The OFF‐score ATPFs increased with the PV correction (from 9 to 13, 99% specificity); most likely the result of more specific reference limit predictions combined with the altitude‐induced increase in red cell production. Importantly, all abnormal biomarker values were identified by a low confidence value. Although the multifaceted, individual physiological response to altitude confounded some results, the PV model appears capable of reducing the impact of PV fluctuations on [Hb].
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 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 it