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What is the role of hydroxychloroquine in reducing thrombotic risk in patients with antiphospholipid antibodies?

2016· review· en· W2558859036 on OpenAlex
Tzu‐Fei Wang, Wendy Lim

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHematology · 2016
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHydroxychloroquineMedicineAntibodyAntiphospholipid syndromeThrombosisImmunologyInternal medicineDiseaseCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

Abstract A 35-year-old man presents with an acute unprovoked deep vein thrombosis of the left lower extremity. He is treated with anticoagulation and elects to discontinue treatment after 6 months. He subsequently develops polyarthralgias, fatigue, and a malar rash, and a diagnosis of systemic lupus erythematosus is made based on laboratory and clinical findings. Additional laboratory testing reveals persistent triple positive antiphospholipid antibodies, including lupus anticoagulant, high titer anticardiolipin antibodies, and anti–β2-glycoprotein I antibodies. The patient is reinitiated on anticoagulation, and the patient’s rheumatologist inquires if the addition of hydroxychloroquine could help to prevent recurrent thrombosis.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.701
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.319
Teacher spread0.301 · 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