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Record W7064447579

Assessing the impact of heatwave exposure on the swimming performance, kinematics, and metabolism of a nearshore marine fish, Cymatogaster aggregata

2023· other· en· W7064447579 on OpenAlexfundno aff

Bibliographic record

VenueResearchWorks at the University of Washington (University of Washington) · 2023
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaGroupe de recherche interuniversitaire en limnologieUniversity of GlasgowBritish Ecological SocietyFonds de recherche du Québec – Nature et technologiesUniversity of WashingtonTrent UniversityEcological Society of AmericaFisheries Society of the British IslesNational Science Foundation
KeywordsEnergeticsMetabolic rateRange (aeronautics)PerchEnergy metabolismBioenergeticsAir temperatureClimate change
DOInot available

Abstract

fetched live from OpenAlex

The severity and frequency of marine heatwaves (MHWs) have increased drastically across the globe, with some of the most intense heatwaves happening within the last decade. The consequences of MHWs vary in severity and include range shifts and diet changes as well as mortality events in marine species. In fishes, elevated temperatures can lead to changes in whole-animal metabolism and performance metrics. However, the impact of temperature on a key performance metric, optimal swim speed (Uopt) is not fully understood. Here, we investigate how heatwave exposure (I.e., +2°C and +4°C) over a five-day period affects the metabolic rate and swimming performance of the shiner perch (Cymatogaster aggregata) using a swimming respirometer. Preliminary findings demonstrated that Uopt slightly increased following moderate MHW exposure (+2°C) and plateaued at higher MHW exposure (+4°C). However, metabolic costs and maximum swimming speed peaked following moderate MHW exposure and declined under more intense MHWs. Not only does this provide more information on the swimming energetics and performance of a common nearshore species, but it also provides insight into heat tolerance and how this species may respond to future projected marine heatwaves.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0300.000

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 head0.020
GPT teacher head0.254
Teacher spread0.234 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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