Recording body temperature in koalas (<i>Phascolarctos cinereus</i>): a comparison of techniques
Bibliographic record
Abstract
Objective Compare the use of four techniques to measure body temperature in koalas: intraperitoneal (thermal data logger and temperature sensitive radio transmitter), rectal (certified thermometer), tympanic (infrared thermometer), and hind foot (infrared camera). Methods The body temperature data collected concurrently from the intraperitoneal loggers were used as the benchmark in the analyses. Results The rectal, foot and tympanic methods consistently recorded lower body temperature when compared with the benchmark. There was a strong positive relationship (R 2 = 0.79) between logger and rectal measurements, but no significant relationship between logger and foot or logger and tympanic measurements. Conclusion Rectal measurements can be used to record internal body temperature, with the caveat that such measurements will generally register a temperature approximately 0.25°C lower than the actual intraperitoneal temperature.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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 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".