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Record W4396918700 · doi:10.1093/jcag/gwae013

Practical guidance for managing patients with moderate-to-severe ulcerative colitis using small molecule therapies

2024· review· en· W4396918700 on OpenAlexaff
Vipul Jairath, Waqqas Afif, Brian Bressler, Janet Pope, Daniel Selchen, Laura E. Targownik, Remo Panaccione

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMount Sinai HospitalUniversity of British ColumbiaUniversity of CalgarySt. Joseph's HospitalMcGill UniversityMontreal General HospitalUniversity of TorontoSt Joseph's Health CareSt. Michael's HospitalWestern University
FundersBristol-Myers Squibb
KeywordsUlcerative colitisMedicineQuality of life (healthcare)Janus kinaseImmune systemDiseaseSphingosine-1-phosphateIntensive care medicineColitisBioinformaticsSphingosineImmunologyReceptorInternal medicineBiology

Abstract

fetched live from OpenAlex

Ulcerative colitis (UC) is a severe and debilitating illness that affects the quality of life and physical health of many Canadians. Given the dynamic and progressive nature of the disease, advanced therapies are required to support its long-term management. The emergence of small molecule therapies offers novel treatment options that target mechanisms central to the immunopathology of UC. Sphingosine-1-phosphate (S1P) receptor modulators and Janus-activated kinase inhibitors are 2 classes of therapies that target unique pathways to attenuate inflammation and modulate the immune response characteristic of UC. This review aims to provide practical guidance on how these therapeutic options can best be used to optimize treatment management and highlight the emerging role of small molecule therapies as a treatment strategy for UC.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.004

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 head0.019
GPT teacher head0.281
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Canadian Association of GastroenterologySame topicInflammatory Bowel DiseaseFrench-language works237,207