Physiologic Responses in Healthy Labrador Retrievers during Field Trial Training and Competition
Bibliographic record
Abstract
Ten healthy Labrador Retrievers (4 females and 6 males aged 3-6.5 years [mean, 4.5 years]) training with a professional trainer were studied. The dogs were in training during the entire study. Dogs were monitored within 5 minutes after retrieving birds on land and in water on 2 consecutive days during training and on 2 consecutive days at the Atlanta Retriever Club Fall Field Trial. Baseline samples were taken in the morning on a separate day before the dogs were loaded onto a truck. Venous samples were analyzed with a portable blood analyzer. Measurements included hematocrit, sodium, potassium, chloride, blood urea nitrogen (BUN), glucose, lactate, blood pH, Pco2, Po2, HCO3, and TCO2 plus rectal temperature, pulse rate, and respiratory rate. Ambient temperatures were recorded. Distances and times were estimated. Compared to baseline, significant increases occurred in rectal temperature, pulse rate, respiratory rate, chloride, lactate, and pH postexercise (P < .05): sodium, potassium, BUN, Pco2, and TCO2 were significantly decreased postexercise. Blood pH was markedly higher after retrieves on land than after retrieves in water. Estimated mean speeds were 11.4 mph (18.3 km/h) during a triple retrieve on land and 5.6 mph (9.0 km/h) during a retrieve in water. Maximal ambient temperatures were 84-86 degrees F (29-30 degrees C). In summary, Labrador Retrievers training with a professional trainer had evidence of hyperthermia, respiratory alkalosis, hypocapnia, and mild metabolic acidosis monitored within 5 minutes postexercise during training and field trial competition when maximal ambient temperatures were 85 degrees F (29 degrees C). The results provide a baseline against which physiologic responses of dogs with poor performance can be compared.
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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) | 0.001 | 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".