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Record W4412098625 · doi:10.1002/aff2.70079

Pathogens From Salmon Aquaculture in Relation to Conservation of Wild Pacific Salmon in Canada: An Alternative Perspective

2025· article· en· W4412098625 on OpenAlexaffabout
Gary D. Marty, Jayde A. Ferguson, Theodore R. Meyers, Thomas B. Waltzek, Michael L. Kent, Esteban Soto

Bibliographic record

VenueAquaculture Fish and Fisheries · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsAbbotsford Veterinary Clinic
Fundersnot available
KeywordsAquacultureFisheryPerspective (graphical)Relation (database)Fish <Actinopterygii>BiologyGeography

Abstract

fetched live from OpenAlex

ABSTRACT Several articles over the last two decades have provided data, analyses and interpretations that suggest there are significant impacts of pathogens transmitted from farmed salmon on wild Pacific salmon populations in British Columbia (BC), the westernmost province of Canada. Because disease is a normal part of all animal populations, there is always a potential for pathogen transfer between animal populations that interact. However, the evidence is weak that pathogens transmitted from farmed salmon cause significant impacts on wild salmon populations. We provide additional data and alternative interpretations of the available evidence to show that (i) many studies overestimate the risk of pathogens transmitted from farmed salmon to wild Pacific salmon, (ii) these risks have not manifested as having significant impacts on wild Pacific salmon populations, and, therefore, (iii) the evidence better supports the conclusion that pathogens transmitted from farmed salmon are having no more than minimal impact on wild Pacific salmon populations. On the basis of this information, we hypothesize that removing open net pen salmon farms will have no detectable effect on wild Pacific salmon population productivity in relation to reference 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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.535

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 studies0.0000.000
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 head0.008
GPT teacher head0.206
Teacher spread0.199 · 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 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
Published2025
Admission routes2
Has abstractyes

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