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Record W1985453075 · doi:10.1086/521085

An Energy‐Based Body Temperature Threshold between Torpor and Normothermia for Small Mammals

2007· article· en· W1985453075 on OpenAlexaff
Craig K. R. Willis

Bibliographic record

VenuePhysiological and Biochemical Zoology · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsTorporMetabolic rateBiologyEnergy metabolismEnergy expenditureComparative physiologyPhysicsThermodynamicsAnimal sciencePhysiologyEndocrinologyThermoregulation

Abstract

fetched live from OpenAlex

Field studies of use of torpor by heterothermic endotherms suffer from the lack of a standardized threshold differentiating torpid body temperatures (T(b)) from normothermic T(b)'s. This threshold can be more readily observed if metabolic rate (MR) is measured in the laboratory. I digitized figures from the literature that depicted simultaneous traces of MR and T(b) from 32 respirometry runs for 14 mammal species. For each graph, I quantified the T(b) measured when MR first began to drop at the onset of torpor (T(b-onset)). I used a general linear model to quantify the effect of ambient temperature (T(a)) and body mass (BM) on T(b-onset). For species lighter than 70 g, the model was highly significant and was described by the equation Tb-onset=(0.055+/-0.014)BM+(0.071+/-0.031)Ta+(31.823+/-0.740). To be conservative, I recommend use of these model parameters minus 1 standard error, which modifies the equation to Tb-onset-1 SE=(0.041)BM+(0.040)Ta+31.083. This approach provides a standardized threshold for differentiating torpor from normothermia that is based on use of energy, the actual currency of interest for studies of torpor in the wild. Few laboratory studies have presented the time-course data required to quantify T(b-onset), so more data are needed to validate this relationship.

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 categoriesnone
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 score0.847
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.237
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations102
Published2007
Admission routes1
Has abstractyes

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