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Record W1978145102 · doi:10.1098/rsbl.2008.0641

Latent inhibition of predator recognition by embryonic amphibians

2008· article· en· W1978145102 on OpenAlexaff
Maud C. O. Ferrari, Douglas P. Chivers

Bibliographic record

VenueBiology Letters · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSalamanderBiologyPredationAmphibianPredatorTiger salamanderCaudataLarvaEcologyHatchingZoology

Abstract

fetched live from OpenAlex

To avoid being captured, prey animals need to be able to distinguish predators from non-predators. Recent studies have shown that amphibians can learn to recognize their future predators while in the egg. Here, we investigated whether amphibians would similarly be able to learn to recognize non-predators while in the egg. We exposed newly laid wood frog eggs to the odour of tiger salamander or a water control daily for 5 days. After hatching, the wood frog larvae were raised for two weeks at which time we tried to condition them to recognize the salamander as a predator. Larvae were exposed to injured conspecific cues paired with salamander odour, a well-established mode of learning for aquatic prey. When subsequently tested for their response to salamander odour, the larvae pre-exposed to water as embryos showed significant anti-predator responses. However, larvae pre-exposed to the salamander odour as embryos showed no learning of the predator, indicating that they had already learned to recognize the salamander as a non-predator. These results indicate that amphibian embryos can (i) learn to recognize stimuli as non-threatening and (ii) remember it for at least two weeks. The widespread ability of prey to learn to recognize non-predators might explain the persistence of injured conspecific cues as a reliable mechanism for learned predator recognition.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.142

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.034
GPT teacher head0.214
Teacher spread0.180 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations60
Published2008
Admission routes1
Has abstractyes

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