MétaCan
Menu
Back to cohort

KIRs and autoimmune disease: studies in systemic lupus erythematosus and scleroderma

2007· article· en· W2086736191 on OpenAlexaff
Fawnda Pellett, Fotios Siannis, I. Vukin, P. Lee, Murray B. Urowitz, Dafna D. Gladman

Bibliographic record

VenueTissue Antigens · 2007
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity Health NetworkUniversity of TorontoMount Sinai HospitalToronto Western Hospital
Fundersnot available
KeywordsMedicineImmunologyScleroderma (fungus)ReceptorAutoimmune diseaseHuman leukocyte antigenLupus erythematosusConnective tissue diseaseAntibodyAntigenInternal medicine

Abstract

fetched live from OpenAlex

We investigated killer immunoglobulin-like receptors (KIRs) and the human leukocyte antigen (HLA)-C ligands for the corresponding inhibitory KIRs in Caucasian patients, 304 with systemic lupus erythematosus (SLE) and 90 with scleroderma [or progressive systemic sclerosis (PSS)] compared with 416 Caucasian controls. Compared with controls, KIR2DS1 in the absence of KIR2DS2 was increased in both SLE (P= 0.04) and PSS (P= 0.02). Only 42% of KIR2DS1-positive PSS patients had the appropriate HLA-C ligand for the corresponding inhibitory KIR compared with 61% of KIR2DS1 positive controls (P= 0.02). In the PSS group the presence of at least either activating KIR2DS1 and/or 2DS2 was significantly increased in patients when compared with controls (P= 0.001). This suggests that KIR receptors play a role in susceptibility to both PSS and SLE.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.289
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 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

Citations72
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueTissue AntigensSame topicImmune Cell Function and InteractionFrench-language works237,207