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Record W4414568405 · doi:10.1016/j.mrrev.2025.108564

Mortality rate and causes of death in inborn errors of immunity: A systematic review and meta-analysis

2025· review· en· W4414568405 on OpenAlexaff
Saba Fekrvand, Zahra Esfahani, Ali Saeedi‐Boroujeni, Helia Salehi, Ali Hakimelahi, Amir Almasi‐Hashiani, M. Rahmati, Sanaz Afshar-Ghasemlou, Najmeh Nameh Goshay Fard, Fateme Tarighat Monfared, Ehsan Khoshnezhad Afkham, Nazanin Fathi, Tannaz Moeini Shad, Fateme Babaha, Farzad Nazari, Matineh Nirouei, Amir Salehi Farid, Negin Sanadgol, Hosein Rafiemanesh, Mahsa Yousefpour Marzbali, Gholamreza Hassanpour, Peter Olbrich, Antonio Condino-Neto, Tomohiro Morio, Andrew R. Gennery, Isabelle Meyts, H D Ochs, Hassan Abolhassani, Reza Yazdani

Bibliographic record

VenueMutation Research/Reviews in Mutation Research · 2025
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsUniversity of OttawaQueen's University
FundersTehran University of Medical Sciences and Health ServicesFonds Wetenschappelijk Onderzoek
KeywordsMortality rateImmune systemPhagocyteDiseaseComponent (thermodynamics)Function (biology)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.030
Bibliometrics0.0040.006
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.322
GPT teacher head0.510
Teacher spread0.189 · 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 designMeta-analysis
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
Published2025
Admission routes1
Has abstractno

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