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Enzyme-Linked Immunosorbent Assay Based on a Chimeric Antigen Bearing Antigenic Regions of Structural Proteins E <sup>rns</sup> and E2 for Serodiagnosis of Classical Swine Fever Virus Infection

2005· article· en· W2144025702 on OpenAlexaboutno aff
Min Lin, Erin Trottier, Maria Mallory

Bibliographic record

VenueClinical and Vaccine Immunology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsVirologyAntigenClassical swine feverBiologyVirusFusion proteinEpitopeSerologyAntibodyRecombinant DNAImmunologyGeneBiochemistry

Abstract

fetched live from OpenAlex

The antigenic region (residues 109 to 160) of classical swine fever virus (CSFV) protein E(rns) and the N-terminal antigenic region (residues 1 to 136) of protein E2 were constructed in the form of a fused, chimeric protein, C21E(rns)E2, for use as an enzyme-linked immunosorbent assay (ELISA) antigen for the serodiagnosis of CSFV infection. Tested with 238 negative-field (CSFV-free) sera from Canadian sources, the specificity of the ELISA was determined to be 93.7%. All 20 sera from experimentally infected pigs representing a variety of animals, virus strains, and days postinfection (dpi; range, 7 to 210) were detected as positive (100%). In contrast, an ELISA based on an E(rns) fragment (E(rns)(aa 109-160)) or an E2 fragment (E2(aa 1-221)) identified only 18 (90%) of 20 sera from infected pigs as positive, missing two targets collected at 7 dpi. These data suggest that use of the chimeric antigen C21E(rns)E2 would improve serodiagnostic sensitivity and allow for the detection of CSFV infection as early as 7 dpi.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.047
GPT teacher head0.308
Teacher spread0.260 · 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

Citations17
Published2005
Admission routes1
Has abstractyes

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