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Record W2604356311 · doi:10.1139/cjfas-2017-0006

Effects of acidic pH on wild, farmed, and F1 hybrid Atlantic salmon (<i>Salmo salar</i>) parr

2017· article· en· W2604356311 on OpenAlexaffvenueabout
L. Lush, Isabel Costa, Kimberly Marshall, Juan C. Pérez-Casanova, Rénald Belley, Dounia Hamoutene

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsSalmoIntrogressionHybridBiologyAquacultureOffspringFish farmingSmoltificationFisherySalmonidaeFish <Actinopterygii>ZoologyBotanyGeneGeneticsPregnancy

Abstract

fetched live from OpenAlex

Farmed escapees have the potential to introduce novel genes to wild salmon and alter locally adapted populations. We tested whether the acidic conditions found in rivers on Newfoundland’s south coast might differentially impact offspring of farmed Atlantic salmon (Salmo salar) in comparison to wild populations. We performed crosses with wild and farmed parents to obtain wild (W♂ × W♀), farmed (F♂ × F♀), and F1 hybrid (W♂ × F♀, F♂ × W♀) parr and conducted a common garden experiment at neutral or acidic pH. No differences were observed between pure wild crosses and F1 hybrids, suggesting that acidic waters do not differentially affect survival, growth, condition factor, and Na+/K+-ATPase activity of F1 hybrids. Trends in mortality show that pure farmed parr had lower survival than pure wild and F1 hybrids in low pH. Considering that production of F1 hybrids rather than pure farmed offspring is the most likely outcome in the wild, pure farmed parr survival may have little bearing on the prediction of genetic risks of farmed–wild interactions. There is no evidence to indicate that the survival of the F1 generation in acidic waters acts as a potential barrier against introgression.

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 score0.011
Threshold uncertainty score0.023

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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

Citations0
Published2017
Admission routes3
Has abstractyes

Explore more

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