MEAN CORPUSCULAR VOLUME (MCV) AND RED BLOOD CELL DISTRIBUTION WIDTH (RDW) IN QUARTER HORSES USED FOR BARREL RACING
Bibliographic record
Abstract
Abstract Twenty-two Quarter Horses, eight females and 14 males, 4.88±2.42 years old and weighting 430.0±31.4 kg, were evaluated before (T0), 5 minutes (T1), 30 minutes (T2), and 120 minutes (T3) after a barrel racing exercise to determine the influence of physical exercise on the mean corpuscular volume (MCV) and red blood cell distribution width (RDW). Variables were analyzed and comparisons were made using Tukey test, considering p<0.05. Comparisons between males and females were done using t-test. Mean MCV values were 46.5 ± 2.0 fl for T0, 47.6 ± 2.2 fl for T1, 46.6 ± 1.8 fl for T2, and 46.7 ± 1.9 fl for T3 for males, and 46.3 ± 0.6 fl on T0, 47.7 ± 0.9 fl on T1, 46.7 ± 0.8 fl on T2, and 46.4 ± 0.8 fl on T2 for females. Mean RDW values were 28.8 ± 8.1% for T0, 30.8 ± 9.5% for T1, 28.2 ± 8.1% for T2, and 26.6 ± 8.0% for T3 for males, and 28.0 ± 7.3% for T0, 27.1 ± 8.1% for T1, 28.1 ± 8.1% for T2, and 28.6 ± 7.2% for T3 on females. A significant increase for MCV on both males and females was observed. No differences were observed between values recorded on males and females for MCV and RDW. It was possible to conclude the physical activity imposed on the present research leaded to a homogeneous macrocytosis.
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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 | 0.000 | 0.001 |
| 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".