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Record W2151847893 · doi:10.7202/706004ar

Characterization of a monoclonal antibody to turnip mosaic virus and its use in immunodiagnosis of infection

2005· article· en· W2151847893 on OpenAlexaffvenue
Peter Horsewood, Mark R. McDermott, L. W. Stobbs, P.L.J. Brais, Brian J. Underdown

Bibliographic record

VenuePhytoprotection · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsMcMaster UniversityVineland Research and Innovation CentreQuebec Society for the Protection of Plants
Fundersnot available
KeywordsMonoclonal antibodyTurnip mosaic virusImmunoassayVirologyBiologyAntibodyVirusclone (Java method)Plant virusPotyvirusDNABiochemistryImmunology

Abstract

fetched live from OpenAlex

Monoclonal antibodies specifie for turnip mosaic virus (TuMV) were produced and used in a double antibody sandwich enzyme immunoassay to detect virus in infected plants. One particular antibody from a hybridoma clone having desirable growth, specificity and antibody production properties was characterized in detail. This antibody was shown by immunocytochemical electron microscopy and immunoblotting to react with a virion coat protein. Conditions providing efficient extraction of virus from leaves were investigated by using the antibody in both capture and detection steps of a sandwich immunoassay. With an extraction buffer System containing multiple detergents, a highly sensitive assay was produced that reliably detected virus in infected plants. This assay is now in routine use for immunodiagnosis of turnip mosaic virus infections.

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 score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.038
GPT teacher head0.275
Teacher spread0.236 · 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

Citations5
Published2005
Admission routes2
Has abstractyes

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