Respiratory alkalosis and primary hypocapnia in Labrador Retrievers participating in field trials in high–ambient-temperature conditions
Bibliographic record
Abstract
OBJECTIVE: To determine whether Labrador Retrievers participating in field trials develop respiratory alkalosis and hypocapnia primarily in conditions of high ambient temperatures. ANIMALS: 16 Labrador Retrievers. PROCEDURES: At each of 5 field trials, 5 to 10 dogs were monitored during a test (retrieval of birds over a variable distance on land [1,076 to 2,200 m]; 36 assessments); ambient temperatures ranged from 2.2 degrees to 29.4 degrees C. For each dog, rectal temperature was measured and a venous blood sample was collected in a heparinized syringe within 5 minutes of test completion. Blood samples were analyzed on site for Hct; pH; sodium, potassium, ionized calcium, glucose, lactate, bicarbonate, and total CO2 concentrations; and values of PvO2 and PvCO2. Scatterplots of each variable versus ambient temperature were reviewed. Regression analysis was used to evaluate the effect of ambient temperature (< or = 21 degrees C and > 21 degrees C) on each variable. RESULTS: Compared with findings at ambient temperatures < or = 21 degrees C, venous blood pH was increased (mean, 7.521 vs 7.349) and PvCO2 was decreased (mean, 17.8 vs 29.3 mm Hg) at temperatures > 21 degrees C; rectal temperature did not differ. Two dogs developed signs of heat stress in 1 test at an ambient temperature of 29 degrees C; their rectal temperatures were higher and PvCO2 values were lower than findings in other dogs. CONCLUSIONS AND CLINICAL RELEVANCE: When running distances frequently encountered at field trials, healthy Labrador Retrievers developed hyperthermia regardless of ambient temperature. Dogs developed respiratory alkalosis and hypocapnia at ambient temperatures > 21 degrees C.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".