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Record W3037459643 · doi:10.1021/acsinfecdis.0c00332

Progress toward the Development of Glycan-Based Vaccines against Campylobacteriosis

2020· review· en· W3037459643 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Infectious Diseases · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsInstitut National de la Recherche Scientifique
FundersFonds de recherche du Québec – Nature et technologiesFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of Canada
KeywordsCampylobacteriosisGlycanMedicineCampylobacter jejuniIntensive care medicineBiologyComputational biologyImmunologyBacteria

Abstract

fetched live from OpenAlex

As one of the main causes of bacterial diarrhea and a major risk factor for triggering Guillain–Barré autoimmune syndrome, campylobacteriosis, that is, Campylobacter spp. infections, represents a major health issue worldwide. There is thus a pressing need for developing an effective and broad-coverage campylobacteriosis vaccine. Campylobacter jejuni, an encapsulated, multidrug resistant Gram-negative bacterium, expresses virulence-associated capsular polysaccharides (CPSs), which constitute exquisite targets for the design of glycoconjugate vaccines. In that context, synthetic carbohydrate chemistry acts as a crucial enabling technology for the preparation of homogeneous constructs while allowing antigenic epitopes to be deciphered and probed at the molecular level. This review aims at covering recent developments in CPS-based campylobacteriosis vaccines as well as in the total syntheses of C. jejuni-related mono- and oligosaccharide mimics.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.294
Teacher spread0.246 · 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