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Record W4386752945 · doi:10.1002/ece3.10526

Pelvic spine reduction affects diet but not gill raker morphology in two polymorphic brook stickleback ( <i>Culaea inconstans</i> ) populations

2023· article· en· W4386752945 on OpenAlexafffund
Jonathan A. Mee, Emily Yap, Daniel M. Wuitchik

Bibliographic record

VenueEcology and Evolution · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsMount Royal University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSticklebackBiologySPINE (molecular biology)ZoologyBenthic zoneFish <Actinopterygii>EcologyFisheryBioinformatics

Abstract

fetched live from OpenAlex

Pelvic spine polymorphism occurs in several species in the stickleback family (Gasterosteidae). Given the similar phenotypic polymorphisms in multiple stickleback species, we sought to determine the extent of parallelism in the ecological correlates of pelvic spine reduction. Based on a metabarcoding analysis of brook stickleback gut contents in two polymorphic populations, we found that significant diet differences were associated with pelvic spine reduction, but we found no clear or consistent trend supporting a tendency for benthic feeding in pelvic-reduced brook sticklebacks. These results contrast with those found in threespine sticklebacks where pelvic spine reduction is often associated with a benthic diet. Hence, we found non-parallel consequences of spine polymorphism across species. Furthermore, a difference in gill raker morphology has been frequently observed between ecomorphs with different diets in many fish species. However, we found no evidence of any difference in gill raker morphology associated with pelvic spine polymorphism in brook sticklebacks.

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)0.000
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.236
Teacher spread0.220 · 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

Citations4
Published2023
Admission routes2
Has abstractyes

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