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Record W2005777658 · doi:10.1037/0735-7036.121.2.123

Death feigning by grass snakes (Natrix natrix) in response to handling by human "predators."

2007· article· en· W2005777658 on OpenAlexafffund
Patrick T. Gregory, Leigh Anne Isaac, Richard A. Griffiths

Bibliographic record

VenueJournal of comparative psychology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAmphibian and Reptile Biology
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsNatrixHatchlingPredationBiologyEctothermZoologyEcology

Abstract

fetched live from OpenAlex

Death feigning, a variant of tonic immobility, is usually interpreted as a last-resort antipredator measure. The authors describe death feigning in grass snakes (Natrix natrix) and test some of its potential correlates. Death feigning was seen in 66% of wild-caught snakes but was not seen in hatchlings from laboratory-incubated eggs. Minimal indication of death feigning was mouth gaping, often with the tongue hanging free, but more dramatic cases involved voluntary supination and/or lack of muscle tone. Aside from hatchlings, which did not feign death, there was little variation in frequency or intensity of death feigning with body size. There was no effect of body temperature on death feigning nor were snakes that were moving when caught less likely to feign death than those that were not moving. Interpretation of the adaptive value of death feigning in grass snakes or in other animals is hampered by lack of evidence of this behavior in the field in response to natural 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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.032
GPT teacher head0.375
Teacher spread0.343 · 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

Citations43
Published2007
Admission routes2
Has abstractyes

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