Infrared thermography cannot be used to approximate core body temperature in wild primates
Bibliographic record
Abstract
ABSTRACT Understanding the physiological processes that underpin primate performance is key if we are to assess how a primate might respond when navigating new and changing environments. Given the connection between an animal’s ability to thermoregulate and the changing demands of its thermal environment, increasing attention is being devoted to the study of thermoregulatory processes as a means to assess primate performance. Infrared thermography can be used to record the body surface temperatures of free-ranging animals. However, some uncertainty remains as to how these measurements can be used to approximate core body temperature. Here, we use data collected from wild vervet monkeys ( Chlorocebus pygerythrus ) to examine the relationship between infrared body surface, core body, and local climate, to determine to what extent surface temperatures reflect core body temperature. While we report a positive association between surface and core body temperature – a finding that has previously been used to justify the use of surface temperature measurements as a proxy for core temperature regulation – when we controlled for the effect of the local climate in our analyses, this relationship was no longer observed. That is, body surface temperatures were solely predicted by local climate, and not core body temperatures, suggesting that surface temperatures tell us more about the environment a primate is in, and less about the thermal status of its body core in that environment. Despite the advantages of a non-invasive means to detect and record animal temperatures, infrared thermography alone cannot be used to approximate core body temperature in wild primates.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".