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Record W4414112187 · doi:10.1097/opx.0000000000002292

Advances in glaucoma research feature issue

2025· article· en· W4414112187 on OpenAlexaboutno aff
Jonathan Denniss, John G. Flanagan

Bibliographic record

VenueOptometry and Vision Science · 2025
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsGlaucomaFeature (linguistics)Intraocular pressureEye careVision sciencePsychological interventionClinical PracticeSight

Abstract

fetched live from OpenAlex

The 2024 three-year plan for Optometry & Vision Science included increasing the number of feature issues,1 and the journal has already published four high-level and well-received feature issues on: Advances in Vision Impairment Research in June 2024. Advances in Ocular Surface Research in September 2024 Aging, the Eye and Vision System in February 2025 Advances in Refractive Error Research in May 2025. We are excited to say that our next feature issue is on advances in glaucoma research. The world of glaucoma research continues to move quickly. Over the last 25 years, we have seen the redefinition of glaucoma as a neurodegenerative disease, imaging of retinal changes in previously unimaginable detail, have redefined normal tension glaucoma, improved functional testing, have new clinical guidelines, developed new pharmacological, laser, and surgical treatments, have new ways to measure intraocular pressure and examine the anterior chamber angle, and have seen the dawn of artificial intelligence, home monitoring, and personalized medicine. Especially pertinent to Optometry & Vision Science, in many parts of the world, we have seen optometrists take a leading role in the treatment and management of glaucoma, expanding and enhancing care provision. There is a great excitement that the next decade will see current research in neuroinflammation, neuroprotection, and neurorestoration lead to cures and eventually sight restoration. Boosting mitochondrial function, helping the retina to heal itself, clinical imaging at the cellular level, and tailoring interventions to the type and stage of disease are all approaches offering hope to our patients. These advances sit alongside ever-improving diagnostic and monitoring techniques, improved care pathways, and better understanding of how glaucoma affects vision and the daily activities of those with the disease. We invite you to join us in ensuring that the feature issue on advances in glaucoma research will disseminate, educate, and help prepare us all to understand the progress that is shaping our future clinical impact. DEADLINE The deadline for submission of papers to this feature issue is November 3, 2025. We are happy to accept submissions after the deadline, but late submissions requiring major revisions may not complete the peer review process in time for inclusion in the feature issue. Of course, if a slightly late submission received a “minor revision” decision, it would very likely be published in the feature issue. PUBLICATION ONLINE BEFORE THE ISSUE Each individual paper is published online quickly after acceptance and appears in the pre-publication area of Optometry & Vision Science’s webpages (https://journals.lww.com/optvissci/toc/pre-publication). The feature issue itself will then likely be published in the May or June 2026 issue. TOPICAL AREAS Our team of feature issue editors has highlighted several areas that we would particularly keen to receive submissions in. These include: AI and glaucoma Bioinformatics and glaucoma Diagnostics and disease detection Evaluating progression and disease management Innovative case series Disease mechanisms Clinical psychophysics, including perimetry Imaging (including Optical Coherence Tomography, Optical Coherence Tomography Angiography, adaptive optics, and oximetry) Animal models Cell and molecular biology Neuroinflammation, neuroprotection, and neuroregeneration Quality of life and task performance THE FEATURE ISSUE EDITORS The glaucoma research feature issue team is: Jonathan Denniss, University of Bradford, Bradford, United Kingdom, lead co-editor. John Flanagan, University of California at Berkeley, Berkley, California, lead co-editor. Bang Bui, The University of Melbourne, Victoria, Australia. Brad Fortune, Devers Eye Institute, Portland, Oregon. Danica Marrelli, University of Houston, Houston, Texas. Nimesh Patel, University of Houston, Houston, Texas. Jeremy Sivak, University of Toronto, Toronto, Canada. Joanne Wood, Queensland University of Technology, Queensland, Australia. Please pass on this call for papers to colleagues who may be interested in submitting papers. Please prepare submissions according to the Instructions for Authors: https://edmgr.ovid.com/ovs/accounts/ifauth.htm and submit them online at https://www.editorialmanager.com/ovs/default2.aspx, noting that your paper is being submitted for consideration of this feature issue.

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)0.001
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 score0.113
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.001
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 head0.013
GPT teacher head0.483
Teacher spread0.470 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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