MétaCan
Menu
Back to cohort

The morphological plastic response to water current velocity varies with age and sexual state in juvenile Atlantic salmon, <i>Salmo salar</i>

2008· article· en· W2092144365 on OpenAlexaff
David J. Páez, Richard D. Hedger, Louis Bernatchez, Julian J. Dodson

Bibliographic record

VenueFreshwater Biology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSalmoJuvenileHabitatBiologyCurrent (fluid)Phenotypic plasticityEcologyDragSalmonidaeSexual maturityFisheryZoologyFish <Actinopterygii>OceanographyGeologyPhysics

Abstract

fetched live from OpenAlex

Summary 1. Salmonids, like many other fish species, exhibit morphological plasticity to variations in water current velocity. However, little is known about how this response varies with age and alternative sexual tactics that usually coexist in the same area. We therefore sampled immature 1‐ and 2‐year‐old and sexually mature Salmo salar parr to determine how the morphological response to slow and rapid water currents varies across these groups. 2. Both 1‐ and 2‐year‐old immature parr in rapid habitats can be distinguished from individuals in slow habitats using a combination of fin measurements. In contrast, body shape measurements were useful only to distinguish 2‐year‐old individuals in the different habitat types. We also showed that mature parr are notably robust, irrespective of habitat type. For these individuals, only their body length differed between slow and rapid water currents, being bigger in slow water currents. 3. Our results imply that fins are the first structures to respond to water current velocity, followed by changes in body shape as individuals grow bigger. The robust phenotype observed for mature parr is likely to pose extra limitations on movement due to an increase in drag forces, thus contributing to their smaller size in rapid water currents.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.221
Teacher spread0.207 · 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.

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

Citations28
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueFreshwater BiologySame topicFish Ecology and Management StudiesFrench-language works237,207