Insights into animal temperature adaptations revealed through thermal imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AbstractInfrared thermal technology allows for the real-time visualisation of fixed or transient changes in the long-wave radiative energy emanating from an object, in essence, allowing for the estimation of surface temperature. Animal surface temperatures are, therefore, readily detected using this technology, allowing for the assessment of physiological responses associated with the regulation of body temperature. In this paper, we will introduce some recent advances made possible or enhanced through the use of thermal imaging. In particular, this imaging technology has shed light on the regulation of peripheral blood flow in endothermic animals, on the dynamics of animal heat transfer in complex thermal environments, on the production of heat associated with metabolism and on the importance of evaporative heat loss to respiratory function and its potential contribution to preventing overheating of the brain. More than a simple imager for temperature, this technology has the potential to contribute a greater understanding of animal thermal adaptations, not only since it provides live information on surface temperatures, but more importantly because its non-invasive nature which allows measurements to be obtained with minimal disturbance.Keywords: THERMOREGULATIONPERIPHERAL HEAT LOSSINFRARED THERMAL IMAGINGMAMMALBIRDREPTILE
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it