MétaCan
Menu
Back to cohort
Record W1493334324 · doi:10.1093/pch/11.2.110

Questions and answers on immunization

2006· article· en· W1493334324 on OpenAlexaffabout
Stéphane Paulus, MB BS Dphil FRCPC Stuart Turvey

Bibliographic record

VenuePaediatrics & Child Health · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsImmunizationMedicineImmunologyAntibody

Abstract

fetched live from OpenAlex

QUESTION: Does regular topical use of tacrolimus or pimecrolimus alter the antibody response to immunization? COMMENT: Atopic dermatitis (AD) is a common chronic inflammatory skin disease that causes significant suffering and has limited treatment options. Because of a perception by physicians and patients that topical tacrolimus (Protopic, Astellas Pharma Canada) and pimecrolimus (Elidel, Novartis Pharmaceuticals Canada Inc) are safer than steroid preparations, abetted by heavy direct-to-consumer advertising, these topical immunomodulators (TIMs) have been increasingly used as first-line therapy in paediatrics. TIMs are indicated for children two years and older with refractory AD, or those who have experienced local or systemic side effects with topical steroids. TIMs act by suppressing T cell and mast cell activation, inhibiting inflammatory cytokine release and downregulating aberrant expression of high-affinity immunoglobulin E receptors on Langerhans cells. In early 2005, public attention was focused on these new medications when the United States Food and Drug Administration posted an advisory warning of a potential cancer risk from the use of TIMs (1,2). This advisory was based on animal studies, case reports in a small number of patients and mechanisms of action of the drugs. Beyond the possible cancer risk, many other questions are now being raised concerning these new medications, including whether TIMs have any effect on the immune response following immunization.

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 score0.297
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.005
GPT teacher head0.239
Teacher spread0.234 · 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
Published2006
Admission routes2
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicTransgenic Plants and ApplicationsFrench-language works237,207