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Record W2567949255 · doi:10.1016/j.jaci.2016.10.033

A novel kindred with inherited STAT2 deficiency and severe viral illness

2017· letter· en· W2567949255 on OpenAlexfundno aff
Leen Moens, Lien Van Eyck, Dirk Jochmans, Tania Mitera, Glynis Frans, Xavier Bossuyt, Patrick Matthys, Johan Neyts, Michael J. Ciancanelli, Shen‐Ying Zhang, Rik Gijsbers, Jean‐Laurent Casanova, Stéphanie Boisson‐Dupuis, Isabelle Meyts, Adrian Liston

Bibliographic record

VenueJournal of Allergy and Clinical Immunology · 2017
Typeletter
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsnot available
FundersUniversitaire Ziekenhuizen Leuven, KU LeuvenGenentechVlaamse regeringAssistance publique-Hôpitaux de ParisVlaams Instituut voor BiotechnologieSt. Giles FoundationKU LeuvenFonds Wetenschappelijk OnderzoekInstitut des maladies génétiques ImagineBaxaltaCSL BehringHospital for Sick ChildrenPfizerGilead SciencesSanofiUniversité Paris DescartesBiogenHoward Hughes Medical Institute
KeywordsMedicineMeaslesRubellaImmunologySTAT2STAT1VirologyInterferonVaccinationBiologySTAT proteinGeneticsSignal transduction

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.275
Teacher spread0.256 · 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 designCase report
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

Citations77
Published2017
Admission routes1
Has abstractno

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