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Record W4403163009 · doi:10.1242/jeb.247703

Hyperoxia does not improve the acute upper thermal tolerance of a tropical marine fish (<i>Lutjanus apodus</i>)

2024· article· en· W4403163009 on OpenAlexafffund
Rebeccah M. Sandrelli, Emma S. Porter, A. Kurt Gamperl

Bibliographic record

VenueJournal of Experimental Biology · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMemorial University of Newfoundland
FundersH2020 European Research CouncilNatural Sciences and Engineering Research Council of CanadaMemorial University of Newfoundland
KeywordsRespirometerHyperoxiaTropical marine climateCritical thermal maximumBiologySciaenidaeRespirometryTemperate climateHypoxia (environmental)MangroveLutjanidaeFisheryFish <Actinopterygii>EcologyRespirationBotanyOxygenChemistry

Abstract

fetched live from OpenAlex

Fish can experience hyperoxia in shallow environments due to photosynthetic activity and this has been suggested to provide them with a metabolic refuge during acute warming. However, this hypothesis has never been tested on a tropical marine species. Thus, we fitted 29°C-acclimated wild schoolmaster snapper (Lutjanus apodus; a species known to experience diel hyperoxia in mangrove creeks and coastal waters) with Transonic® flow probes and exposed them to an acute increase in temperature (at 1°C h-1) in respirometers under normoxia and hyperoxia (150% air saturation), until their critical thermal maximum (CTmax). The CTmax of both groups was ∼39°C, and no differences in maximum cardiac function were recorded as the fish were warmed. However, temperature-induced factorial aerobic scope was significantly greater in fish tested under hyperoxia. These data suggest that hyperoxia will not protect coastal tropical fish species during marine heat waves, despite its effects on metabolic scope/capacity.

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 score0.009

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)0.0030.000

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 head0.010
GPT teacher head0.249
Teacher spread0.239 · 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

Citations5
Published2024
Admission routes2
Has abstractyes

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