MétaCan
Menu
← Back to cohort
Record W4409359536 · doi:10.1139/cjfas-2024-0327

Thermal acclimation and its reversal in early life stages of brook trout

2025· article· en· W4409359536 on OpenAlexafffundvenue
Emily R. Lechner, Erin Stewart, Chris C. Wilson, Graham D. Raby

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsMinistry of Natural Resources and ForestryTrent University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTroutAcclimatizationBiologyFisheryEcologyEnvironmental scienceFish <Actinopterygii>Zoology

Abstract

fetched live from OpenAlex

In juvenile and adult fishes, the initiation, completion, and reversal of acclimation have been studied but there are few data on the dynamics of acclimation in early life stages. We examined how chronic warming during incubation altered thermal tolerance in early life stages of brook trout ( Salvelinus fontinalis) to quantify the scope and duration of thermal acclimation and carryover effects during early development. We assessed how quickly the acclimation of upper thermal tolerance (CTmax) was lost once hatched larvae were moved to common conditions. In embryos, and 4 weeks after hatch, fish in warmer treatments had a positive acclimation response (higher CTmax). Eight weeks after hatch, acclimation was completely reversed, whereby fry that had been reared in ambient (cooler) conditions had higher thermal tolerance than those from warm treatments. Early life stages of brook trout can acclimate their thermal tolerance throughout development but acclimation to warmer temperatures can have a cost in the form of lower body condition.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.217
Teacher spread0.197 · 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 designBench or experimental
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
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicAquaculture Nutrition and Growth→French-language works237,207→