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Record W2894681060 · doi:10.22215/etd/2014-10269

An Investigation into the Ecology and Evolution of Caterpillar Eyespots

2014· dissertation· en· W2894681060 on OpenAlexafffund
Thomas J. Hossie

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCarleton University
FundersUniversity of GuelphNatural Sciences and Engineering Research Council of CanadaNorthwestern University
KeywordsEyespotMimicryAposematismCaterpillarBiologyPredationEcologyPredatorAdaptation (eye)ZoologyLarvaNeuroscience

Abstract

fetched live from OpenAlex

Eyespots are conspicuous circular patterns on the body of an animal which superficially resemble vertebrate eyes.These odd markings have long captured the interest of biologists and naturalists alike, many of whom have suggested that eyespots mimic the real eyes of dangerous animals and thereby protect prey species from their attackers.Eyespots are particularly widespread and diverse in lepidopteran caterpillars, and these caterpillars with eyespots are typically assumed to be snake-mimics.Yet a dearth of empirical investigation has left us without evidence that eyespots can protect caterpillars, or the ability to substantiate our subjective belief that these caterpillars are mimicking snakes.Using a combination of field and lab experiments 2 Chapter: Eyespots interact with body colour to protect caterpillarlike prey from avian predators

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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.015
GPT teacher head0.213
Teacher spread0.198 · 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

Citations2
Published2014
Admission routes2
Has abstractyes

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