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Record W2107015219 · doi:10.1177/104063870401600214

Interlaboratory Testing of Porcine Sera for Antibodies to Porcine Circovirus Type 2

2004· article· en· W2107015219 on OpenAlexaffabout
I. McNair, Michelle Marshall, F. McNeilly, Anette Bøtner, A.-S. Ladekjær-Mikkelsen, Isabelle Vincent, Brigitte Herrmann, Romeo E Sanchez, Carrie Rhodes

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPorcine circovirusTiterImmunoperoxidaseVirologyAntibodyAntibody titerBiologySerologyDirect fluorescent antibodyVirusCircovirusImmunologyMonoclonal antibody

Abstract

fetched live from OpenAlex

A panel of 20 porcine sera was distributed to 5 laboratories across Europe and Canada. Each center was requested to test the sera for the presence of porcine circovirus type 2 antibodies using the routine assays, indirect immunofluorescence assay (IFA) and indirect immunoperoxidase monolayer assay (IPMA), and to determine the titer of each serum. Results from all centers were then compiled and correlated. They demonstrate a wide variation in the titers obtained between laboratories. These differences were dependent on the assay used and the choice of fixative. In general, IPMA gave higher titers than did IFA, and paraformaldehyde gave higher titers than did acetone or ethyl alcohol. This report highlights the need for standardized procedures and biologicals for this virus.

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)0.011
metaresearch head score (Gemma)0.009
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 score0.011
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.082
GPT teacher head0.294
Teacher spread0.211 · 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".

Quick stats

Citations20
Published2004
Admission routes2
Has abstractyes

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