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Record W2790698850 · doi:10.1177/2040622318759282

Interleukin 23 in the skin: role in psoriasis pathogenesis and selective interleukin 23 blockade as treatment

2018· article· en· W2790698850 on OpenAlexfundno aff
Tom C. Chan, Jason E. Hawkes, James G. Krueger

Bibliographic record

VenueTherapeutic Advances in Chronic Disease · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPsoriasis: Treatment and Pathogenesis
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesDermiraRegeneron PharmaceuticalsCelgeneValeant Pharmaceuticals InternationalSanofiEli Lilly and CompanyAmgen
KeywordsPsoriasisMedicinePathogenesisInterleukin 23Interleukin 17ImmunologyImmune systemDiseaseInterleukinPlaque psoriasisDermatologyCytokinePathology

Abstract

fetched live from OpenAlex

Plaque psoriasis is one of the most common autoimmune skin diseases and is characterized by erythematous, scaly plaques. Many highly effective, targeted therapies have been developed as a result of an improved understanding of the pathogenesis of psoriasis. Using agents that target the central interleukin (IL)-23/IL-17 immune axis, this once difficult-to-treat disease is now among the most effectively treated autoimmune diseases with major clinical improvements possible in around 90% of patients. In this article, we outline the immune mechanisms responsible for the development of psoriasis and provide an overview of the novel IL-23 antagonists being used to manage this chronic skin 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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.

Study designOther design
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

Citations135
Published2018
Admission routes1
Has abstractyes

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