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Record W2897139358 · doi:10.1139/cjfas-2018-0334

Cardiac SERCA activity in sockeye salmon populations: an adaptive response to migration conditions

2018· article· en· W2897139358 on OpenAlexafffundvenue
Katja Anttila, Anthony P. Farrell, David A. Patterson, Scott G. Hinch, Erika J. Eliason

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaKoneen Säätiö
KeywordsSERCAOncorhynchusBiologyInternal medicineEndoplasmic reticulumSemelparity and iteroparityATPaseEcologyFish <Actinopterygii>FisheryCell biologyReproductionMedicineBiochemistryEnzyme

Abstract

fetched live from OpenAlex

We show that cardiac sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) activity differs considerably among sockeye salmon (Oncorhynchus nerka) populations. Variability in SERCA activity was significantly correlated with elevation gain and temperature during migration, as well as maximum cardiac stroke volume. Furthermore, because SERCA activity was not lowered during the spawning migration, this aspect of the cardiac contraction machinery is apparently spared during the senescence of these semelparous salmon, likely because it is essential for these fish to complete spawning. Only when spawning had been completed was there a significant reduction in SERCA activity, which was detectable in males at a 25 °C and in females at a 15 °C assay temperature. Hence, we propose that migration conditions act as a strong selective force that has resulted in local adaptation of myocardial SERCA activity among sockeye salmon populations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

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 head0.032
GPT teacher head0.262
Teacher spread0.230 · 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

Citations15
Published2018
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→