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Record W2275790899 · doi:10.1139/cjz-2015-0168

Some like it hot? Developmental differences in Yellow-bellied Toad (<i>Bombina variegata</i>) tadpoles from geographically close but different habitats

2016· article· en· W2275790899 on OpenAlexvenueno aff
C. Dittrich, Sanja Drakulić, M.P. Schellenberg, J. Thein, Mark‐Oliver Rödel

Bibliographic record

VenueCanadian Journal of Zoology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersBundesamt für Naturschutz
KeywordsBiologyHabitatTadpole (physics)EcologyPopulationAmphibianPhenotypic plasticityLarvaToadBufoEctothermMetamorphosisZoology

Abstract

fetched live from OpenAlex

The key for the long-term survival of species is their potential to respond to changing conditions. These reactions are usually species-specific and may vary between populations. The Yellow-bellied Toad (Bombina variegata (L., 1758)) occurs in forested and open areas. We wanted to know whether tadpoles react plastically to different environmental conditions, and if so, whether reaction norms are species, population, or season specific. In a common garden experiment, we compared developmental traits (developmental time, size, body condition) of metamorphs from different habitats (forest vs. quarry) in close geographic proximity. Tadpoles from both habitats grew up under shaded and sunny conditions. The experiments were run during early and late breeding season. We detected different developmental strategies between populations, concerning treatments and season on a microgeographic scale. Tadpoles with quarry origin developed faster and reached larger body sizes, at the expense of lower body condition. Major risks affecting tadpole’s survival in the open habitat are high temperatures and high desiccation. Forest tadpoles were comparatively smaller in size, but showed higher plasticity and higher body condition. Under changing climatic conditions, quarry population may reach temperatures above their thermal limits. In contrast, forest conditions may mitigate increasing temperatures. Forest populations could be better adapted to future climate change.

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 score0.004
Threshold uncertainty score0.009

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 head0.018
GPT teacher head0.194
Teacher spread0.176 · 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

Citations29
Published2016
Admission routes1
Has abstractyes

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