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Record W4353087415 · doi:10.54097/hset.v36i.6273

Development of Vaccines in Celiac Disease Therapies

2023· article· en· W4353087415 on OpenAlexaff
Chengjia Zhu

Bibliographic record

VenueHighlights in Science Engineering and Technology · 2023
Typearticle
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiseaseMedicineGlutenClinical trialImmunologyIntensive care medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

In Western countries, celiac disease is a relatively common genetic immune disorder. When a patient ingests foods containing gluten, the gluten protein acts as an allergen and can cause the patient to develop the disease. The disease is not directly fatal, but its onset can be very uncomfortable for the patient, and its complications may lead to an increased chance of developing certain cancers. A lifetime gluten-free diet has already been the standard course to prevent celiac disease symptoms, but it can be challenging. In past studies, researchers have attempted to prevent patients from developing or mitigating their condition through vaccines as a treatment. However, with research stagnating and clinical trials being canceled, the production of a celiac disease vaccine is currently experiencing a bottleneck. Fortunately, the treatment of celiac disease is not the only way to build tolerance through vaccines; other therapies under investigation as well as new vaccine design ideas may be effective in treating celiac disease. This review systematically summarizes the scientific status of the celiac disease and discusses the potential of vaccine as a promising treatment for celiac disease.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.270
Teacher spread0.258 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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