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Estimation of the repeatability and reproducibility of three diagnostic tests for infectious salmon anaemia virus

2005· article· en· W2060811549 on OpenAlexaff
Pascale Nérette, Ian R. Dohoo, K. Larry Hammell, Nellie Gagné, Patricia A. Barbash, S. MacLean, Carmencita Yason

Bibliographic record

VenueJournal of Fish Diseases · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsFisheries and Oceans CanadaUniversity of Prince Edward Island
Fundersnot available
KeywordsRepeatabilityReproducibilityBiologyMcNemar's testKappaVeterinary medicineMedicineChromatographyStatisticsMathematicsChemistry

Abstract

fetched live from OpenAlex

Reverse transcriptase polymerase chain reaction (RT-PCR), virus isolation (VI) and indirect fluorescent antibody tests (IFAT) are three assays currently used by the salmon industry to identify fish infected with infectious salmon anaemia virus (ISAV). However, no data are available on the repeatability (within-laboratory consistency) and reproducibility (between-laboratory consistency) of these assays and very limited information is available on the effect of freezing samples on test results. In order to evaluate these assays, five laboratories participated in a blinded study of 400 kidney samples representing four populations of farmed Atlantic salmon with different prevalence of ISAV. Each laboratory used its own testing protocols. Repeatability and reproducibility were evaluated using kappa as the measure of agreement. The effect of freezing was evaluated using the McNemar test. Freezing did not affect VI but improved the sensitivity of RT-PCR. The repeatability and reproducibility of VI was almost perfect. There was a substantial difference in repeatability of RT-PCR among the three laboratories with kappa ranging from 0.5 to 0.96. The repeatability for RT-PCR was generally low. The repeatability of IFAT was moderate when the results were analysed using 1+ and above as a positive result. The results of the study show the need to standardize the protocol and interpretation of RT-PCR.

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)0.005
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 score0.158
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 head0.012
GPT teacher head0.257
Teacher spread0.245 · 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

Citations18
Published2005
Admission routes1
Has abstractyes

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