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Record W2067330296 · doi:10.1111/eth.12132

Once Bitten, Twice Shy: Does Previous Experience Influence Behavioural Decisions of Snakes in Encounters with Predators?

2013· article· en· W2067330296 on OpenAlexafffund
Patrick T. Gregory

Bibliographic record

VenueEthology · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsPredationNatrixOphidiaPredatorBiologyPredator avoidanceEcologyZoologyForaging

Abstract

fetched live from OpenAlex

Abstract Injuries are common in animals of diverse taxa and are usually attributed to encounters with predators. Although often non‐lethal, injuries nevertheless represent effects of predators that can have negative consequences for demography and fitness (e.g. reproductive costs). However, encounters with predators also represent experience through which animals can learn and positively adapt their future behaviour, potentially mitigating, at least partly, the negative effects of prior exposure to predators. I predicted that injured grass snakes ( Natrix natrix ), which presumably had been handled previously by a predator, would be more likely to move before capture than uninjured snakes. This prediction was borne out. Snakes with injuries also had lower body condition than uninjured snakes, although the effect was non‐significant. Snakes that had been previously captured also were significantly more likely to move before capture than snakes that had never been caught before. These results provide strong evidence for the role of experience and learning in modifying the antipredator behaviour of snakes.

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)0.003
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.260
Teacher spread0.236 · 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

Citations16
Published2013
Admission routes2
Has abstractyes

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