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Record W2784181451 · doi:10.1139/cjz-2016-0314

Adrenocortical and bioenergetic responses to cold in laboratory-born northern red-backed voles (<i>Myodes rutilus</i>) from two populations in south Siberia, Russia

2018· article· en· W2784181451 on OpenAlexvenueno aff
Ivan A. Polikarpov, Tatiana V. Titova, E. Yu. Kondratyuk, Е. А. Новиков

Bibliographic record

VenueCanadian Journal of Zoology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyArvicolinaeVoleRutilusZoologyCaptivityPopulationBioenergeticsCorticosteroneEcologyMicrotusBank volePopulation densityFish <Actinopterygii>EndocrinologyGeneticsFisheryDemography

Abstract

fetched live from OpenAlex

In animal populations inhabiting ecologically suboptimal environmental conditions, phenotypical shifts in physiological traits responsible for coping with environmental challenges can be expected. If such variations are of heritable origin, then they will manifest themselves even in individuals bred in captivity. In laboratory-born red-backed voles (Myodes rutilus (Pallas, 1779)) originating from a population with constantly low density, maximum cold-induced metabolic rates were higher than in voles from a high-density population, similar to the data obtained on wild-caught individuals from the same populations. However, unlike wild-caught voles, in laboratory-born individuals maintained under comfortable conditions, we revealed no interpopulation differences either in basal plasma corticosterone level or in corticosterone response to acute cooling. These data confirm the suggestion about the heritable origin of increased maximum cold-induced metabolic rate in a red-backed vole population with relatively low density.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.240
Teacher spread0.216 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Zoology→Same topicBat Biology and Ecology Studies→French-language works237,207→