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Record W2128899493 · doi:10.2108/zsj.30.118

Thermographic Analysis of Body Surface Temperature of Mammals

2013· article· en· W2128899493 on OpenAlexaff
Jacopo P. Mortola

Bibliographic record

VenueZOOLOGICAL SCIENCE · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMcGill University
Fundersnot available
KeywordsBody surfaceConvectionThermographyNatural convectionRadiationThermoregulationBiologyAtmospheric sciencesRadiant heatMaterials scienceMeteorologyInfraredEcologyGeometryOpticsPhysicsMathematics

Abstract

fetched live from OpenAlex

Among mammals, the similarity in body temperature indicates that body size differences in heat loss must match the body size differences in heat production. This study tested the possibility that body surface temperature (Tbs), responsible for heat loss through radiation and convection, may vary systematically with the animal's body mass (M). Tbs was measured by whole body thermography in 53 specimens from 37 eutherian mammals ranging in M from a few grams to several tons. Numerous thermographs were taken from all angles, indoor, with the animals standing still in absence of air convection and of external radiant sources, at the ambient temperature of 20-22°C, 22-25°C, or 25-27°C. Data were analysed as whole body surface average, as average of the "effective" body surface area (those regions with temperatures exceeding ambient temperature by > 1.5°C or by > 5°C), as the peak histogram distribution and as average of the regions with the top 20% temperature values. For all modes of data analysis and at all ambient temperatures Tbs was independent of the animal's M. From these data, the heat loss by radiation and natural convection combined was estimated to vary to the 2/3 power of M. It is concluded that, for the same ambient conditions, the surface temperature responsible for radiation and convection is essentially body-size independent among mammals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.010
GPT teacher head0.221
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2013
Admission routes1
Has abstractyes

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