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Record W4403059101 · doi:10.58931/crt.2024.1147

Management of Rheumatologic Immune-Related Adverse Events (Rh-irAEs) – An Overview of Immunosuppressive Therapies

2024· article· en· W4403059101 on OpenAlexaff
Shahin Jamal, Jenny Li, Marie Hudson, Carrie Ye

Bibliographic record

VenueCanadian rheumatology today. · 2024
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsJewish General HospitalUniversity of British ColumbiaUniversity of AlbertaArthritis Research Centre of CanadaResearch Canada
Fundersnot available
KeywordsAdverse effectMedicineImmune systemDermatologyIntensive care medicineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Cancer treatment has entered a new era with the expanding role of immunotherapy, in particular immune checkpoint inhibitors (ICIs). ICIs, including those that target cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), programmed death protein-1 (PD-1), and programmed death ligand-1 (PD-L1), work by blocking the intrinsic down-regulators of the immune system, leading to sustained activation of effector T-cells to enhance endogenous anti-tumour immune responses.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.023
GPT teacher head0.296
Teacher spread0.272 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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