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Record W2795295655 · doi:10.3354/dao03224

Assessment of intra-specific variability in Saprolegnia parasitica populations of aquaculture facilities in British Columbia, Canada

2018· article· en· W2795295655 on OpenAlexaffabout
Paul Y. de la Bastide, Cayla Naumann, William E. Hintz

Bibliographic record

VenueDiseases of Aquatic Organisms · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBiologyAquaculturePopulationSaprolegniaOutbreakEcologyMicrosatellitePopulation geneticsGenetic diversityZoologyFisheryFish <Actinopterygii>Genetics

Abstract

fetched live from OpenAlex

Among the Saprolegnia species found in aquaculture facilities, S. parasitica is recognized as the primary fish pathogen and remains an ongoing concern in fish health management. Until recently, these pathogens were kept in check by use of malachite green; due to its toxicity, this chemical has now been banned from use in many countries. It is difficult to predict and control S. parasitica outbreaks in freshwater systems and there is a need to understand the population genetic structure of this pathogen. Genetic characterization of this species in aquaculture systems would provide information to track introductions and determine possible sources of inoculum. Degenerate PCR primers containing short sequence repeats were used to create microsatellite-associated genetic markers (random amplified microsatellites) for the comparison of S. parasitica isolates collected primarily from commercial Atlantic salmon aquaculture systems in British Columbia, Canada, over a 15 mo period to describe their spatial and temporal variability. The frequencies of amplified products were compared and the population genetic diversity was measured using Nei's genetic distance and Shannon's information index, while the species population structure was evaluated by phylogenetic analysis. S. parasitica was detected in all facilities sampled. Genetic diversity was low but not clonal, most likely due to repeated introduction events and a low level of sexual recombination over time. A better understanding of pathogen population structure will assist the development of effective preventative measures and targeted treatments for disease outbreaks.

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 score0.033
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.010
GPT teacher head0.278
Teacher spread0.268 · 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

Citations8
Published2018
Admission routes2
Has abstractyes

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