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Record W2992334319 · doi:10.3899/jrheum.181375

Hydroxychloroquine Ocular Toxicity: Lessons Learned

2019· article· en· W2992334319 on OpenAlexvenueno aff
Jeff Rabin, Kirsti Ramirez

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Ocular Toxicity
Canadian institutionsnot available
Fundersnot available
KeywordsHydroxychloroquineMedicineRetinopathyToxicityOphthalmologyDermatologyOptometryCoronavirus disease 2019 (COVID-19)Internal medicineEndocrinology

Abstract

fetched live from OpenAlex

Hydroxychloroquine (HCQ) is efficacious for various diseases1,2, but can produce “bulls-eye” retinopathy that decreases vision even after discontinuance3,4. Retinopathy can be present in 7.5% of patients after 5 or more years of HCQ treatment, increasing to 20% after 20 years2. In 2016, the American Academy of Ophthalmology published new recommendations for the evaluation of HCQ, emphasizing dosage based on body weight (≤ 5 mg/kg)5. We describe a case in which dosage …

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.308
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations5
Published2019
Admission routes1
Has abstractyes

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