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Record W2270881563 · doi:10.1111/jfd.12429

Long‐term epidemiological survey of <i>Kudoa thyrsites</i> (Myxozoa) in Atlantic salmon (<i>Salmo salar</i> L.) from commercial aquaculture farms

2015· article· en· W2270881563 on OpenAlexaffabout
Wyth L. Marshall, Ariadna Sitjà‐Bobadilla, H. Brown, Tiffany MacWilliam, Zina Richmond, Heather M. Lamson, Diane Morrison, Luis O.B. Afonso

Bibliographic record

VenueJournal of Fish Diseases · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyxozoan Parasites in Aquatic Species
Canadian institutionsMinistry of ForestsBC Centre for Aquatic Health Sciences
Fundersnot available
KeywordsSalmoMyxozoaBiologyAquacultureAnimal scienceVeterinary medicineFish farmingParasite hostingFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Kudoa thyrsites (Myxozoa) encysts within myocytes of a variety of fishes. While infected fish appear unharmed, parasite-derived enzymes degrade the flesh post-mortem. In regions of British Columbia (BC), Canada, up to 4-7% of fillets can be affected, thus having economic consequences and impacting the competitiveness of BC's farms. K. thyrsites was monitored in two farms having high (HP) or low (LP) historical infection prevalence. At each farm, 30 fish were sampled monthly for blood and muscle during the first year followed by nine samplings during year two. Prevalence and intensity were measured by PCR and histology of muscle samples. In parallel, fillet tests were used to quantify myoliquefaction. Infections were detected by PCR after 355 and 509 degree days at LP and HP farms, respectively. Prevalence reached 100% at the HP farm by 2265 degree days and declined during the second year, whereas it plateaued near 50% at the LP farm. Infection intensities decreased after 1 year at both farms. Blood was PCR-positive at both farms between 778 and 1113 degree days and again after 2000 degree days. This is the first monitoring project in a production environment and compares data between farms with different prevalence.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.058
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.041
GPT teacher head0.308
Teacher spread0.267 · 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

Citations26
Published2015
Admission routes2
Has abstractyes

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