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Record W4294838806 · doi:10.1093/biolinnean/blac095

Diversity and evolution of amphibian pupil shapes

2022· article· en· W4294838806 on OpenAlexaff
Kate N. Thomas, Caitlyn Rich, Rachel C. Quock, Jeffrey W. Streicher, David J. Gower, Ryan K. Schott, Matthew K. Fujita, R.H. Douglas, Rayna C. Bell

Bibliographic record

VenueBiological Journal of the Linnean Society · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsYork University
FundersNatural Environment Research CouncilSight Research UK
KeywordsBiologyAmphibianPupilEcologyLarvaMetamorphosisEvolutionary biologyHabitatFunctional diversityOntogenyZoologyNeuroscience

Abstract

fetched live from OpenAlex

Abstract Pupil constriction has important functional consequences for animal vision, yet the evolutionary mechanisms underlying diverse pupil sizes and shapes are poorly understood. We aimed to quantify the diversity and evolution of pupil shapes among amphibians and to test for potential correlations to ecology based on functional hypotheses. Using photographs, we surveyed pupil shape across adults of 1294 amphibian species, 74 families and three orders, and additionally for larval stages for all families of frogs and salamanders with a biphasic ontogeny. For amphibians with a biphasic life history, pupil shape changed in many species that occupy distinct habitats before and after metamorphosis. In addition, non-elongated (circular or diamond) constricted pupils were associated with species inhabiting aquatic or underground environments, and elongated pupils (with vertical or horizontal long axes) were more common in species with larger absolute eye sizes. We propose that amphibians provide a valuable group within which to explore the anatomical, physiological, optical and ecological mechanisms underlying the evolution of pupil shape.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.206
Teacher spread0.184 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueBiological Journal of the Linnean SocietySame topicAmphibian and Reptile BiologyFrench-language works237,207