Physiology and behavior of dogs during air transport.
Bibliographic record
Abstract
Twenty-four beagles were used to measure physiological and behavioral reactions to air transport. Each of 3 groups of 4 sedated (with 0.5 mg/kg body weight of acepromazine maleate) and 4 non-sedated (control) dogs was flown on a separate flight between Montreal, Quebec, and Toronto, Ontario, after being transported by road from Quebec City to Montreal. Saliva and blood samples were taken before ground and air transport and after air transport. The heart rate was monitored during the whole experiment except during ground transport, and behavior was monitored by video during air transport. Sedation did not affect any of the variables measured. The mean plasma cortisol concentration was significantly higher (P < 0.05) after ground transport than at baseline (225.3 vs 134.5 nmol/L); the mean salivary cortisol concentration was significantly higher (P < 0.05) after both ground and air transport than at baseline (16.2 and 14.8, respectively, vs 12.6 nmol/L). The mean neutrophil count was significantly higher (P < 0.05) after both ground and air transport than at baseline (80.6 and 81.4, respectively, vs 69.5 per 100 white blood cells), whereas the mean lymphocyte count was significantly lower (P < 0.05) (13.2 and 13.7, respectively, vs 22.4 per 100 white blood cells). Loading and unloading procedures caused the largest increase in heart rate. On average, the dogs spent more than 50% of the time lying down, and they remained inactive for approximately 75% of the time, except during take-off. These results suggest that transportation is stressful for dogs and that sedation with acepromazine, at the dosage and timing used, does not affect the physiological and behavioral stress responses of dogs to air transport.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".