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Record W4402087507 · doi:10.1038/s41433-024-03312-w

Sustained disease control with aflibercept 8 mg: a new benchmark in the management of retinal neovascular diseases

2024· article· en· W4402087507 on OpenAlex
Jean‐François Korobelnik, Paolo Lanzetta, Charles C. Wykoff, Tien Yin Wong, Xin Zhang, Peter Morgan-Warren, Scott M. Fitzpatrick, Sergio Leal, Lynne R. Brunck, Zoran Hasanbasic, Karen Chu, Kimberly Reed, Sobha Sivaprasad

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

VenueEye · 2024
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsBayer (Canada)
Fundersnot available
KeywordsAfliberceptMedicineOphthalmologyRetinalOptometrySurgeryBevacizumabChemotherapy

Abstract

fetched live from OpenAlex

Retinal neovascular diseases, such as neovascular age-related macular degeneration (nAMD), diabetic retinopathy (DR), diabetic macular oedema (DMO), and retinal vein occlusion (RVO), are major causes of visual impairment worldwide [ 1 , 2 , 3 ]. Vascular endothelial growth factor (VEGF) is considered critical in the pathophysiology of these conditions and randomized trials have established the efficacy and safety of agents with an anti-VEGF mechanism of action [ 4 ]. Extensive real-world studies of ranibizumab or aflibercept 2 mg have also demonstrated that effectiveness in clinical practice is possible [ 5 , 6 , 7 , 8 ], including maintenance of vision gains through 4 years with a proactive treat-and-extend (T&E) regimen in patients with nAMD [ 5 ], and vision gains over 3 years with a meaningful reduction in treatment burden after early, consistent dosing in patients with DMO [ 6 ].

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.259
Teacher spread0.254 · 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