MétaCan
Menu
Back to cohort
Record W2052353221 · doi:10.1159/000077249

Lipopolysaccharide O-Antigen Antibody-Based Detection of the Fish Pathogen <i>Flavobacterium psychrophilum</i>

2003· article· en· W2052353221 on OpenAlexaff
Elizabeth M. Crump, Malcolm B. Perry, Stephen Gale, Evan T. Crawford, William W. Kay

Bibliographic record

VenueMicrobial Physiology · 2003
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsInstitute for Biological SciencesUniversity of Victoria
Fundersnot available
KeywordsPolyclonal antibodiesMicrobiologyAntibodyAntigenBiologyKeyhole limpet hemocyaninFlavobacteriumDirect agglutination testBovine serum albuminPathogenAgglutination (biology)BacteriaImmunologySerology

Abstract

fetched live from OpenAlex

Several yellow-pigmented species within the family Flavobacteriaceae are commonly associated with diseases in fish and are difficult to speciate due to their fastidious, slow-growing nature and cross-reactive antigens. Here we report the development of specific, antibody-diagnostic tests for Flavobacterium psychrophilum, the aetiological agent of rainbow trout fry syndrome and bacterial cold water disease. A unique antigen from F. psychrophilum, the lipopolysaccharide (LPS) O-polysaccharide (O-PS), formed the basis for the antibody test. LPS O-PS was purified and conjugated to keyhole limpet haemocyanin and bovine serum albumin for the generation of rabbit immune sera and the development of antibody-based diagnostic tests. Rabbit polyclonal anti-O-PS serum was highly specific for F. psychrophilum, without the need for prior cross-absorption with related bacteria and was the basis of an effective ELISA diagnostic test. Antibodies were purified from rabbit anti-O-PS serum and adsorbed onto coloured latex beads for the development of a specific, bead agglutination assay for F. psychrophilum.

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)0.000
metaresearch head score (Gemma)0.000
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
Metaresearch0.0000.000
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 integrity0.0010.000
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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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

Citations15
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueMicrobial PhysiologySame topicAquaculture disease management and microbiotaFrench-language works237,207