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Record W3082874975 · doi:10.1139/cjfas-2020-0209

Evidence of prevalent heat stress in Yukon River Chinook salmon

2020· article· en· W3082874975 on OpenAlexvenueaboutno aff
Vanessa R. von Biela, Lizabeth Bowen, Stephen D. McCormick, Michael P. Carey, Daniel Donnelly, Shannon Waters, Amy M. Regish, Sarah M. Laske, Randy J. Brown, Sean Larson, Stanley Zuray, Christian E. Zimmerman

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersU.S. Geological SurveyAlaska Department of Fish and GameArctic-Yukon-Kuskokwim Sustainable Salmon InitiativeMassachusetts Department of Fish and Game
KeywordsChinook windOncorhynchusTributaryHeat stressFisheryPopulationEnvironmental scienceJuvenileBiologyEcologyGeographyFish <Actinopterygii>Animal scienceDemography

Abstract

fetched live from OpenAlex

Migrating adult Pacific salmon (Oncorhynchus spp.) are sensitive to warm water (>18 °C), with a range of consequences from decreased spawning success to early mortality. We examined the proportion of Yukon River Chinook salmon (O. tshawytscha) exhibiting evidence of heat stress to assess the potential that high temperatures contribute to freshwater adult mortality in a northern Pacific salmon population. Water temperatures greater than 18 °C have occurred almost annually in the Yukon River and correspond with low population abundance since the 1990s. Using gene transcription products and heat shock protein 70 biomarkers validated by field experiment, we identified heat stress in half of Chinook salmon examined (54%, n = 477) across three mainstem locations and three tributaries in 2016–2017. Biomarkers tracked wide variation in water temperature (14–23 °C) within a tributary. The proportion of salmon with heat stress differed between years at four of the six locations, with more prevalent heat stress in the warmer year. This work demonstrates that warming water temperatures are currently affecting northern populations of Pacific salmon.

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 score0.871
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
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 head0.031
GPT teacher head0.224
Teacher spread0.194 · 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

Citations44
Published2020
Admission routes2
Has abstractyes

Explore more

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