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Record W4207016536 · doi:10.1016/j.autrev.2022.103055

Eculizumab use in catastrophic antiphospholipid syndrome (CAPS): Descriptive analysis from the “CAPS Registry”

2022· review· en· W4207016536 on OpenAlexfundno aff
Brenda López-Benjume, Ignasi Rodríguez‐Pintó, Mary‐Carmen Amigo, Doruk Erkan, Yehuda Shoenfeld, Ricard Cervera, Gerard Espinosa

Bibliographic record

VenueAutoimmunity Reviews · 2022
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
FundersDepartment of Obstetrics and Gynecology, University of Wisconsin-MadisonSorbonne UniversitéUrmia University of Medical SciencesAkershus UniversitetssykehusCentre hospitalier universitaire Sainte-JustineDebreceni EgyetemMcGill University Health CentreUniversidad Nacional Mayor de San MarcosGdański Uniwersytet MedycznyUniversidade Federal do Rio de JaneiroUniversidade do Estado do Rio de JaneiroShahrekord University of Medical SciencesUniversitetet i OsloMayo ClinicTel Aviv UniversityTaysCatholic University of KoreaKagawa UniversityFundación Valle del LiliCedars-Sinai Medical CenterDepartment of Haematology, Christian Medical College, VelloreUniversidad de AntioquiaUniversity HospitalsCentral Manchester University Hospitals NHS Foundation Trust
KeywordsEculizumabMedicineThrombotic microangiopathyCatastrophic antiphospholipid syndromeAntiphospholipid syndromeAtypical hemolytic uremic syndromeInternal medicinePediatricsAdverse effectSurgeryThrombosisComplement systemImmunologyAntibodyDisease

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)0.003
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.180
GPT teacher head0.366
Teacher spread0.186 · 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
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

Citations86
Published2022
Admission routes1
Has abstractno

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