MétaCan
Menu
Back to cohort

Neuroprotection in Glaucoma: Animal Models and Clinical Trials

2017· review· en· W2732996930 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnnual Review of Vision Science · 2017
Typereview
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsMcGill UniversityUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersCanadian Institutes of Health ResearchNational Institutes of HealthCanada Research ChairsResearch to Prevent Blindness
KeywordsNeuroprotectionGlaucomaMedicineOptic neuropathyOptic nerveRetinal ganglion cellNeuroscienceOphthalmologyIntraocular pressureBlindnessOptometryBiologyPharmacology

Abstract

fetched live from OpenAlex

Glaucoma is a progressive neurodegenerative disease that frequently results in irreversible blindness. Glaucoma causes death of retinal ganglion cells (RGCs) and their axons in the optic nerve, resulting in visual field deficits and eventual loss of visual acuity. Glaucoma is a complex optic neuropathy, and a successful strategy for its treatment requires not only better management of known risk factors such as elevated intraocular pressure and the development of improved tools for detecting RGC injury but also treatments that address this injury (i.e., neuroprotection). Experimental models of glaucoma provide insight into the cellular and molecular mechanisms of glaucomatous optic neuropathy and aid the development of neuroprotective therapies.

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)0.021
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.219
GPT teacher head0.556
Teacher spread0.336 · 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