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Record W1937254863 · doi:10.1670/14-114

Color Pattern Variation in a Cryptic Amphibian,<i>Anaxyrus fowleri</i>

2015· article· en· W1937254863 on OpenAlexaffabout
Mohamad Rabbani, Brigette Zacharczenko, David M. Green

Bibliographic record

VenueJournal of Herpetology · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiologyHabitatEcologyCamouflageAmphibianSpotsDorsumSnoutZoologyBotanyAnatomy

Abstract

fetched live from OpenAlex

Many species of animals employ camouflage to render them inconspicuous. Selection to precisely match cryptic color patterns to the background substrate should result in geographic variation in relation to substrate type. We tested this premise by examining color pattern variation in relation to substrate surface in Fowler's Toad (Anaxyrus fowleri), a noxious and cryptically colored amphibian that is widespread in eastern North America and frequently associated with sandy habitats. We quantified total dorsal spot area, number of spots, and size of the four largest dorsal spots among 330 specimens of Fowler's Toads (89 live, 241 preserved) in 14 samples from Canada and the United States. We found no significant difference in the extent or number of spots between males vs. females or between living vs. preserved specimens after compensating for variation in snout–vent length. However, toads from freshwater habitats with extensive areas of open sandy terrain had significantly smaller and fewer dorsal spots than toads from either seacoast localities with open sands present or toads from freshwater habitats with open sands absent. Because saltwater seaside beaches and sand dunes are generally uninhabitable by amphibians, we take this as evidence consistent with the presence of adaptive background pattern matching coloration in this species.

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 score0.024
Threshold uncertainty score0.047

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 studies0.0000.000
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 head0.038
GPT teacher head0.248
Teacher spread0.210 · 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

Citations14
Published2015
Admission routes2
Has abstractyes

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