Biochemical serum profile of quarter mile equines in team penning training
Bibliographic record
Abstract
The objective of this work was to evaluate the proteins, minerals, metabolites, and serum enzymes profile in Quarter Mile equines subjected to training for Team Penning competitions by comparing the results before and after training. The animals were from the Agricultural Exhibition Park of Uberlândia (CAMARU), in Uberlândia in the State of Minas Gerais, Brazil. These animals perform constant periodic training with an average duration of two and a half hours per training. Blood samples from twenty male and female equines were collected at the beginning and end of a 45-day interval and then analyzed. A 5 mL blood sample from each animal was collected before and after training by a jugular external venipuncture, and the samples were placed in a tube—without anticoagulant and containing separator gel—to obtain the serum. The components analyzed were: total proteins, albumin, globulins, albumin to globulin ratio (A:G), total and ionized calcium, phosphorus, calcium to phosphorus ratio (Ca:P), cholesterol, triglycerides, creatinine, urea, alkaline phosphatase, ɤ-glutamyl transferase, lactate dehydrogenase (LDH), aspartate amino transferase (AST), alanine aminotransferase (ALT) and creatine kinase (CK). Statistical differences were observed with higher values after exercise for total calcium, ionized calcium, Ca: P ratio, creatinine and ALT and decreased concentrations were found for globulins, phosphorus, cholesterol and triglycerides. Despite the changes observed in the serum concentrations of some elements after exercises, it was concluded that the animals were in adequate physical condition to perform the proposed physical exercises.
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 | 0.001 | 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".