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Record W4285014910 · doi:10.1186/s40850-022-00139-4

Light/dark phase influences intra-individual plasticity in maintenance metabolic rate and exploratory behavior independently in the Asiatic toad

2022· article· en· W4285014910 on OpenAlexaff
Song Tan, Juan Li, Qiao Yang, Jinzhong Fu, Jingfeng Chen

Bibliographic record

VenueBMC Zoology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of Guelph
FundersNational Natural Science Foundation of China
KeywordsBivariate analysisPhenotypic plasticityBiologyNocturnalVariance (accounting)EcologyPsychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

BACKGROUND: It is well-known that light/dark phase can affect energy expenditure and behaviors of most organisms; however, its influences on individuality (inter-individual variance) and plasticity (intra-individual variance), as well as their associations remain unclear. To approach this question, we repeatedly measured maintenance metabolic rate (MR), exploratory and risk-taking behaviors across light/dark phase four times using wild-caught female Asiatic toads (Bufo gargarizans), and partitioned their variance components with univariate and bivariate mixed-effects models. RESULTS: The group means of maintenance MR and risk-taking behavior increased at night, while the group mean of exploratory behavior remained constant throughout the day. At night, the intra-individual variances were elevated in maintenance MR but reduced in exploration, suggesting that phenotypic plasticity was enhanced in the former but constrained in the latter. In addition, maintenance MR was not coupled with exploratory or risk-taking behaviors in daytime or at night, neither at the inter-individual nor intra-individual levels. CONCLUSIONS: Our findings suggest that these traits are independently modulated by the light/dark phase, and an allocation energy management model may be applicable in this species. This study sheds new insights into how amphibians adapt nocturnal lifestyle across multiple hierarchy levels via metabolic and behavioral adjustments.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

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