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Record W4307350873 · doi:10.1098/rsbl.2022.0332

Social buffering of the stress response: insights from fishes

2022· review· en· W4307350873 on OpenAlexafffund
Kathleen M. Gilmour, Brittany Bard

Bibliographic record

VenueBiology Letters · 2022
Typereview
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyFight-or-flight responseStress (linguistics)Evolutionary biologyEcologyGeneticsGene

Abstract

fetched live from OpenAlex

Social buffering of stress refers to the effect of a social partner in reducing the cortisol or corticosterone response to a stressor. It has been well studied in mammals, particularly those that form pair bonds. Recent studies on fishes suggest that social buffering of stress also occurs in solitary species, gregarious species that form loose aggregations and species with well-defined social structures and bonds. The diversity of social contexts in which stress buffering has been observed in fishes holds promise to shed light on the evolution of this phenomenon among vertebrates. Equally, the relative simplicity of the fish brain is advantageous for identifying the neural mechanisms responsible for social buffering. In particular, fishes have a relatively small and simple forebrain but the brain regions that are key to social buffering, including the social behaviour network, the amygdala and the hypothalamic-pituitary-adrenal/interrenal axis, are functionally conserved across vertebrates. Thus, we suggest that insight into the mechanistic and evolutionary underpinnings of stress buffering in vertebrates can be gained from the study of social buffering of stress in fishes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.113
GPT teacher head0.398
Teacher spread0.285 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations41
Published2022
Admission routes2
Has abstractyes

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