EVALUATION OF THE ACCURACY OF DIFFERENT METHODS OF MONITORING BODY TEMPERATURE IN ANESTHETIZED BROWN BEARS (<i>URSUS ARCTOS</i>)
Bibliographic record
Abstract
There is some evidence that the handheld rectal thermometer does not accurately measure core temperature in bears. The objective of this study was to compare body temperature measured by the handheld digital thermometer (HDT), deep rectally inserted core temperature capsules (CTCs), and gastrically inserted CTCs in anesthetized brown bears (Ursus arctos). Twenty-two brown bears were immobilized with a combination of zolazepam-tiletamine and xylazine or medetomidine. After immobilization, one CTC was inserted 15 cm deep into the animal's rectum (DRTC) with a standard applicator, and another CTC was inserted into the stomach (GTC) via a gastric tube inserted orally. Temperature was measured every 5-10 min with an HDT. Paired temperature data points were analyzed with the Bland-Altman technique for repeated measurements and regression analysis with a significance level of 0.05. The mean difference ± SD of the difference between HDT and GTC readings was 0.27 ± 0.47 degrees C and the 95% limits of agreement (LoA) were 1.20 and -0.66 degrees C. The determination coefficient (r2) found between these methods was 0.68 (P < 0.0001). The mean difference ± SD of the difference between HDT and DRTC readings was 0.36 ± 0.32 degreesC and the 95% LoA were 1.0 and -0.28 degrees C. The r2 between HDT and DRTC was 0.83 (P < 0.0001). The mean difference ± SD of the difference between the two insertions of the VitalSense capsules was -0.06 ± 0.24 degrees C and the 95% LoA were 0.42 and -0.54 degrees C. The r2 found between GTC and DRTC was 0.91 (P < 0.0001). This study demonstrates that DRTC provided accurate measurement of core temperature and that HDT did not accurately measure core temperature, compared with GTC in anesthetized brown bears.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 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 | 0.000 |
| 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 teacher head, 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".