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Record W4393581438 · doi:10.1098/rspb.2024.0125

Olfactory self-recognition in two species of snake

2024· article· en· W4393581438 on OpenAlexafffund
Troy Freiburger, Noam Miller, Morgan Skinner

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArboreal locomotionBiologyEcologyPredationZoologyHabitat

Abstract

fetched live from OpenAlex

Mark tests, in which an animal uses a mirror to locate and examine an otherwise unnoticeable mark on its own body, are commonly used to assess self-recognition, which may have implications for self-awareness. Recently, several olfactory-reliant species have appeared to pass odour-based versions of the mark test, though it has never been attempted in reptiles. We conducted an odour-based mark test on two species of snakes, Eastern gartersnakes and ball pythons, with widely divergent ecologies (i.e. terrestrial foragers that communally brumate versus semi-arboreal ambush predators that do not). We find that gartersnakes, but not ball pythons, pass the test, and a range of control tests suggest this is based on self-recognition. Gartersnakes are more social than ball pythons, supporting recent suggestions that social species are more likely to self-recognize. These results open the door to examination of the ecology of self-recognition, and suggest that this ability may evolve in response to species-specific ecological challenges, some of which may align with complexity of social structures.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.060
GPT teacher head0.255
Teacher spread0.196 · 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

Citations11
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicAnimal Behavior and ReproductionFrench-language works237,207