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Record W2794370052 · doi:10.1111/jfb.13530

A rainbow trout <scp><i>Oncorhynchus mykiss</i></scp> strain with higher aerobic scope in normoxia also has superior tolerance of hypoxia

2018· article· en· W2794370052 on OpenAlexafffund
Y. Zhang, Timothy M. Healy, Wendy E. Vandersteen, Patricia M. Schulte, Anthony P. Farrell

Bibliographic record

VenueJournal of Fish Biology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversity of the Fraser ValleyUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRainbow troutIntraspecific competitionBiologyCritical thermal maximumHypoxia (environmental)OxygenStrain (injury)TroutZoologyEcologyFish <Actinopterygii>AcclimatizationAnatomyFisheryChemistry

Abstract

fetched live from OpenAlex

This study compared parr from three strains of rainbow trout Oncorhynchus mykiss to examine intraspecific variation in metabolic traits, hypoxia tolerance and upper thermal tolerance in this species. At the strain level, variation in absolute aerobic scope (AAS), critical oxygen level (O 2crit ), incipient lethal oxygen saturation (ILOS) and critical thermal maximum (CT max ) generally exhibited consistent differences among the strains, suggesting the possibility of functional associations among these traits. This possibility was further supported at the individual level by a positive correlation between ILOS and O 2crit and a negative correlation between O 2crit and AAS. These results indicate that intraspecific differences in hypoxia tolerance among strains of O. mykiss may be primarily determined by differences in the ability to maintain oxygen uptake in hypoxia and that variation in aerobic scope in normoxia probably plays a role in determining the ability of these fish to sustain metabolism aerobically as water oxygen saturation is reduced.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.629

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 science0.0000.000
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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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 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

Citations40
Published2018
Admission routes2
Has abstractyes

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