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Record W1977480246 · doi:10.3354/dao02862

Denman Island disease in Washington State, USA: distribution and prevalence in Pacific and Olympia oysters

2015· article· en· W1977480246 on OpenAlexaffabout
R. Elston, Carolyn S. Friedman, Lori Gustafson, Gary R. Meyer, Robin D. Rogers

Bibliographic record

VenueDiseases of Aquatic Organisms · 2015
Typearticle
Languageen
FieldMedicine
TopicParasitic infections in humans and animals
Canadian institutionsFisheries and Oceans Canada
FundersCalifornia Department of Fish and WildlifeWashington Department of Fish and Wildlife
KeywordsCrassostreaBiologyOysterPacific oysterVeterinary medicineFisheryZoology

Abstract

fetched live from OpenAlex

We sampled over 2400 wild, feral, and cultured Pacific oysters Crassostrea gigas and Olympia oysters Ostrea lurida in Washington State, USA, from 2002 to 2006 to estimate the prevalence of infection with Mikrocytos mackini, the causative agent of Denman Island disease. Both histology and qualitative PCR methods were used. Estimates of true prevalence of M. mackini infection in C. gigas, after accounting for imperfect test sensitivity, ranged from mean values of 0 to 10.0% by histology and 0 to 8.4% based on pooled PCR samples. M. mackini was not detected in any of the O. lurida samples. Results suggest a lower prevalence of the pathogen and severity of this oyster disease in Washington than that indicated in previous reports from British Columbia, Canada, potentially attributable to higher seawater temperatures in the Washington sample locations.

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 score0.120
Threshold uncertainty score0.239

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 studies0.0000.000
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 head0.016
GPT teacher head0.272
Teacher spread0.257 · 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
Published2015
Admission routes2
Has abstractyes

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