MétaCan
Menu
Back to cohort
Record W3010875070 · doi:10.1111/ede.12333

Isolating the effects of ontogenetic niche shift on brain size development using pumpkinseed sunfish ecotypes

2020· article· en· W3010875070 on OpenAlexafffund
Caleb J. Axelrod, Frédéric Laberge, Beren W. Robinson

Bibliographic record

VenueEvolution & Development · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOntogenyBiologyJuvenileNicheEcologyEcological nicheBrain sizeEcotypeForagingHabitat

Abstract

fetched live from OpenAlex

A functional relationship between relative brain size and cognitive performance has been hypothesized. However, the influence of ontogenetic niche shifts on cognitive performance is not well understood. Increases in body size can affect niche use but distinguishing nonecologically relevant brain development from effects associated with ecology is difficult. If survival is enhanced by functional changes in ecocognitive performance over ontogeny, then brain size development should track ontogenetic shifts in ecology. We control for nonecologically relevant brain size development by comparing brain growth between two ecotypes of Pumpkinseed sunfish whose ecologies diverge over ontogeny from a shared juvenile niche. Brain size differs between ecotypes from their birth year onwards even though their foraging ecology appears to diverge at age 3. This finding suggests that the eco-cognitive requirements of adult niches shape early life brain growth more than the requirements of juvenile ecology.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.017
GPT teacher head0.231
Teacher spread0.214 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueEvolution & DevelopmentSame topicMarine and fisheries researchFrench-language works237,207