PHYSIOLOGICAL EFFECTS OF AZAPERONE AND MIDAZOLAM ON NETGUN-CAPTURED MULE DEER (ODOCOILEUS HEMIONUS)
Bibliographic record
Abstract
Netgun capture is a commonly used capture method for mule deer (Odocoileus hemionus) in North America. Mortalities during netgun captures are generally low, and most often caused by direct trauma and occasionally fatal capture myopathy. Capture is a stressful event for a wild animal, and subclinical capture myopathy is difficult to measure. The use of tranquilizers during netgun capture is not widespread. We compared physiologic variables from 250 netgun-captured deer (57 males and 193 females) that did or did not receive midazolam and azaperone (mean, 0.14 mg/kg; SD, 0.02 mg/kg; range, 0.08-0.21 mg/kg) at time of capture and before transporting to a processing location, with the goal of evaluating whether drug administration would improve or worsen the physiologic state of the animal. Deer were captured in association with management activities between December 2018 and March 2020, with 132 deer receiving midazolam and azaperone at time of capture. Variables recorded included chase times, time from capture to arrival at the processing location, time from capture to release, serial rectal temperatures, heart rates, respiratory rates, body condition, age, sex, O2 administration, creatine kinase, aspartate aminotransferase, packed cell volume, red blood cell concentration, and hemoglobin, as well as serial venous pH, pCO2, HCO3-, and base excess. All animals were collared with GPS tracking devices and monitored after release. There was no difference in survival after capture between deer that did or did not receive midazolam and azaperone. All animals experienced severe metabolic lactic acidosis, which generally worsened with increasing chase time, highlighting the critical importance of limiting chase times during captures. Drug administration did not influence the degree of metabolic acidosis; however, it appeared to have a favorable effect on several stress-related indices, including rectal temperature, heart rate, respiratory rate, and packed cell volume.
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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) | 0.000 | 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".