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Record W4404892798 · doi:10.1101/2024.11.30.626194

Mechanisms of Social Behavior in the Anti-Social Blind Cavefish ( <i>Astyanax mexicanus</i> )

2024· preprint· en· W4404892798 on OpenAlexaff
Britney Sekulovski, Noam Miller

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicSubterranean biodiversity and taxonomy
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsBiologyEvolutionary biologyZoology

Abstract

fetched live from OpenAlex

Abstract The evolution of social behavior in Astyanax mexicanus , which exists as a sighted, surface-dwelling morph and a blind, cave-dwelling morph, provides a model for understanding how environmental pressures shape social behaviors. We compared the shoaling behavior of blind and surface A. mexicanus to that of zebrafish ( Danio rerio ), and examined the effects of nutritional state and the neuropeptides isotocin (IT) and arginine vasotocin (AVT) on their social behavior. Blind cavefish not only fail to form shoals, but actively avoid conspecifics, with hunger further diminishing their social cohesion. Administration of low doses of AVT and an IT antagonist partially restored social behavior in blind cavefish, reducing distances between individuals, whereas surface fish exhibited minimal or opposite responses to these hormonal manipulations. Our findings suggest that the loss of schooling behavior in blind cavefish is not a consequence of visual impairment alone, as they remain capable of detecting and responding to others. Instead, this behavior likely reflects an adaptive response to their resource-poor, predator-free cave environment, where shoaling may be disadvantageous. The differing responses to social hormones between the morphs indicate that blind cavefish may have lost the motivation to shoal rather than the ability, highlighting how ecological pressures can shape social behavior.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.207
Teacher spread0.174 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

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