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Record W2889524560 · doi:10.22621/cfn.v132i1.2018

Body temperature influences growth rates of Common Gartersnakes (<i>Thamnophis sirtalis</i>)

2018· article· en· W2889524560 on OpenAlexafffundvenue
William D. Halliday, Gabriel Blouin‐Demers

Bibliographic record

VenueThe Canadian Field-Naturalist · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of VictoriaWildlife Conservation Society CanadaUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaNature Conservancy of CanadaNature ConservancyUniversity of Ottawa
KeywordsThamnophis sirtalisEctothermHabitatEcologyBiologyLower bodyOld fieldZoologyEnvironmental science

Abstract

fetched live from OpenAlex

Habitat selection can have large impacts on animal fitness. Temperature is an important aspect of habitat suitability for ectotherms, and temperature differences between habitats can thus lead to fitness differences. Here, we use an experiment with female Common Gartersnakes (Thamnophis sirtalis) to examine the effect of body temperature on change in mass (i.e., growth rate), which is a component of fitness. We placed female gartersnakes in experimental enclosures in old field and in forest and monitored their body temperature and mass throughout the summer. Gartersnakes in old field were warmer than gartersnakes in forest, warmer gartersnakes were more likely to eat earthworms, and warmer gartersnakes gained more mass. We therefore provide evidence that habitat use influences body temperature, and body temperature then influences growth, a component of fitness.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.240
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations2
Published2018
Admission routes3
Has abstractyes

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