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Record W3023868885 · doi:10.1101/2020.05.01.072587

Plasticity, repeatability, and phenotypic correlations of aerobic metabolic traits in a small estuarine fish

2020· preprint· en· W3023868885 on OpenAlexaff
Jessica E. Reemeyer, B. Rees

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsMcGill University
Fundersnot available
KeywordsRepeatabilityFish <Actinopterygii>Phenotypic plasticityBiologyEstuaryPhenotypeFisheryEcologyGeneticsStatisticsMathematicsGene

Abstract

fetched live from OpenAlex

Standard metabolic rate (SMR), maximum metabolic rate (MMR), absolute aerobic scope (AAS), and critical oxygen tension (P crit ) were determined for the Gulf killifish, Fundulus grandis , an ecologically dominant estuarine fish, acclimated to lowered salinity, elevated temperature, and lowered oxygen concentration. Acclimation to low salinity resulted in a small, but significant, elevation of P crit ; acclimation to elevated temperature increased SMR, MMR, AAS, and P crit ; acclimation to low oxygen led to a small increase in SMR, but substantial decreases in MMR, AAS, and P crit . Variation in these metabolic traits among individuals was consistent and repeatable when measured during multiple control exposures over seven months. Trait repeatability was unaffected by acclimation condition suggesting that repeatability of these traits is not context dependent. There were significant phenotypic correlations between specific metabolic traits: SMR was positively correlated with MMR and P crit ; MMR was positively correlated with AAS; and AAS was negatively correlated with P crit . In general, within-individual variation contributed more than among-individual variation to these phenotypic correlations. The effects of acclimation on these traits demonstrate that aerobic metabolism is plastic and influenced by the conditions experienced by these fish in the dynamic habitats in which they occur; however, the repeatability of these traits and the correlations among them suggest that these traits change in ways that maintains the rank order of performance among individuals across a range of environmental variation.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.022
GPT teacher head0.206
Teacher spread0.184 · 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 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

Citations4
Published2020
Admission routes1
Has abstractyes

Explore more

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