Blood Gases and Electrolyte Profile Analysis in Žemaitukai Horses During a Multiday Long-Distance 1500 km Endurance Ride
Bibliographic record
Abstract
Today the most of horse have been tested and used for endurance races; the most competitive are Arabian due to their muscle fibre composition. Foreman argued that long-distance activity results in a discharge which influence acid-base imbalance, fluid and electrolyte loss. Acid-base balance in the body plays a key role in metabolic processes. A detailed analysis of acid-base balance provides a biochemical and physiochemical description of the state of the organism, or of individual organs and tissues within the body. Thus it is imperative to analyze acid-base balance. The aim of this study was the monitoring of the variations of blood acid-base and electrolyte parameters, and the description of the relationship between them during a long-distance 1500 km endurance ride. For the trial purpose, fifteen Žemaitukai horses were used (3 females and 12 males). All endurance rides were 1500 km long. Blood samples were taken from the jugular vein of horses into vacuum-proof tubes (United Kindom) for analysis of blood gas, electrolytes and some hematological parameters. Blood was taken in stages: the day before the ride, then after approximately 300 km of the entire distance and two weeks after the end of the ride. Blood gas and electrolyte concentration was analyzed using a blood gas analyzer EPOC (Canada) immediately after taking of a blood sample.Physical exercise in a long-distance race results a high amount of [H+] changes of pH, develops metabolic acidosis and dehydration, due the volatile acids accumulation in the blood plasma. Dehydration leads to hypoxia, hypercapnia, decreased plasma HCO³- and increased hemoglobin levels. Change of electrolyte levels can result in hyperkalemia and hipornatremia. [...].
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".