Physicochemical analysis of acid–base status during recovery from high-intensity exercise in Standardbred racehorses
Bibliographic record
Abstract
Abstract The present study used the physicochemical approach to characterize the changes in acid–base status that occur in Standardbred racehorses during recovery from high-intensity exercise. Jugular venous blood was sampled from nine Standardbreds in racing condition, at rest and for 2 h following a high-intensity training workout. Plasma [H + ] increased from 39.1±1.0 neq l −1 at rest to 44.8±2.7 neq l −1 at 1 min of recovery. A decreased strong ion difference ([SID]) was the primary contributor to the increased [H + ] immediately at the end of exercise, while increased plasma weak ion concentration ([A tot ]) was a minor contributor to the acidosis. A decreased partial pressure of carbon dioxide (PCO 2 ) at 1 min of recovery had a slight alkalinizing effect. The decreased [SID] at 1 min of recovery was a result of a 15.1±3.1 meq l −1 increase in [lactate − ], as [Na + ] and [K + ] were also increased by 6.5±0.7 and 1.14±0.06 meq l −1 , respectively, at 1 min of recovery. It is concluded that high-intensity exercise and recovery is associated with significant changes in acid–base balance, and that full recovery of many parameters that determine acid–base status requires 60–120 min.
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.
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 | 0.000 | 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) | 0.001 | 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 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".