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Measures of diagnostic precision (repeatability and reproducibility) for three test methods designed to detect spring viremia of carp virus

2021· article· en· W3127953406 on OpenAlexafffundabout
Sharon C. Clouthier, Carol McClure, Tamara Schroeder, Sandra Aldous, Jason W. Allen, Crystal Collette-Belliveau, Shaorong Li, Melissa Lindsay, Eric Anderson

Bibliographic record

VenuePreventive Veterinary Medicine · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of ManitobaUniversity of Prince Edward IslandGovernment of CanadaFisheries and Oceans Canada
FundersFisheries and Oceans Canada
KeywordsRepeatabilityReproducibilityViremiaSpring (device)CarpVirologyBiologyStatisticsFish <Actinopterygii>VirusMathematicsFisheryEngineering

Abstract

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Spring viremia of carp virus (SVCV) is a rhabdovirus of the Sprivivirus genus and the etiological agent of an internationally regulated aquatic animal disease in several fish species, including koi carp Cyprinus carpio L. The virus has a complex lifecycle with both acute and persistent stages of infection and can cause high mortality in affected populations. In this study, the diagnostic repeatability (within laboratory agreement) and reproducibility (between laboratory agreement) of 3 tests were investigated to assess their fitness as SVCV diagnostic tools. The tests, reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays targeting either the SVCV glycoprotein (Q1G) or nucleoprotein (Q2N) genes and virus isolation by cell culture (VI), were performed in a blinded study with four Canadian laboratories. Test panels consisted of duplicate sets of 100 tissue samples collected from 3 SVCV prevalence populations of koi: a low-prevalence negative reference population (n = 20 fish) as well as moderate- (n = 50 fish) and high-prevalence (n = 30 fish) populations of koi experimentally infected with SVCV. The Q1G and Q2N tests were performed with kidney tissue in 3 laboratories and with brain tissue in 1 laboratory whereas pools of kidney, spleen and gill tissues were tested with the VI assay in 2 laboratories. Agreement of binary results was evaluated using the observed proportion of agreement, Cohen's kappa and Gwet's agreement coefficient (AC1) whereas the concordance correlation coefficient (ccc) and Bland Altman's limit of agreement were used to evaluate agreement of the RT-qPCR continuous data. Gwet's AC1 provided a more stable estimate of agreement than Cohen's kappa. Overall, high repeatability (AC1, 0.78-0.90) and reproducibility (AC1, 0.74-0.89) were observed for the Q1G and Q2N tests when kidney tissue was used. Lower agreement estimates of repeatability (AC1, 0.54-0.77) and reproducibility (AC1, 0.50-0.80) were obtained for the VI test. RT-qPCR reproducibility was low with kidney-brain tissue pairs (AC1, 0.09-0.46) and high with inter-test pairs of brain (AC1, 0.76-0.86) or kidney tissue (0.75-0.86). Tissue-specific differences in virus load affected test precision and informed final tissue selection. Repeatability (ccc, 0.94-0.97) and reproducibility (ccc, 0.91-0.97) estimates of agreement for paired continuous data from the RT-qPCR assays were similarly high with kidney tissue and lower with paired brain (ccc, 0.15-0.83) and kidney-brain tissues (ccc, 0.01-0.55). The high precision of Q1G and Q2N with kidney tissue suggests that the tests are performing similarly and are suitable candidates for assessment of their diagnostic accuracy.

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)0.067
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.078
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.135
GPT teacher head0.367
Teacher spread0.232 · 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 designBench or experimental
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".

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Citations6
Published2021
Admission routes3
Has abstractyes

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