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Peptide immunotherapy for allergic diseases

2007· review· en· W1480553072 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.

Bibliographic record

VenueAllergy · 2007
Typereview
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImmunogenicityImmunotherapyMedicineImmunologyAllergenAllergyEpitopeAllergen immunotherapyImmunoglobulin EAntibodyImmune system

Abstract

fetched live from OpenAlex

Specific allergen immunotherapy has been widely practised for almost 100 years. Whilst this approach is disease-modifying and efficacious, the use of whole allergen preparations is associated with an unacceptably high prevalence of allergic adverse events during treatment. Many approaches to reduce the allergenicity of immunotherapy preparations whilst maintaining immunogenicity are under development. One such approach is the use of short synthetic peptides which represent major T-cell epitopes of the allergen. Major potential advantages of this approach include markedly reduced capacity to cross-link immunoglobulin-E and activate mast cells and basophils, and ease of manufacture and standardization. Promising results in preclinical studies have led to the translation of this approach to clinical studies in humans. Peptide immunotherapy is currently under development for allergic and autoimmune diseases.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
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 head0.061
GPT teacher head0.357
Teacher spread0.297 · 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