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Record W3013930853 · doi:10.1089/tmj.2020.0009

Telemedicine for Glaucoma: Guidelines and Recommendations

2020· article· en· W3013930853 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.

Bibliographic record

VenueTelemedicine Journal and e-Health · 2020
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of AlbertaUniversity of British Columbia
FundersNational Eye Institute
KeywordsGlaucomaTelemedicineMedicineGonioscopyOptometryGuidelineFundus photographyIntraocular pressureBlindnessPopulationMedical emergencyHealth careOphthalmologyRetinal

Abstract

fetched live from OpenAlex

Background: Glaucoma is the leading cause of irreversible blindness worldwide. Access to glaucoma specialists is challenging and likely to become more difficult as the population ages. Introduction: Using telemedicine for glaucoma (teleglaucoma) has the potential to increase access to glaucoma care by improving efficiency and decreasing the need for long-distance travel for patients. Results: Teleglaucoma programs can be used for screening, diagnostic consultation, and long-term treatment monitoring. Key components of teleglaucoma programs include patient history, equipment, intraocular pressure measurement, pachymetry, anterior chamber imaging/gonioscopy, fundus photography, retinal nerve fiber layer imaging, medical record and imaging software, and skilled personnel. Discussion: Teleglaucoma has tremendous potential to improve patient access to high-quality cost-effective glaucoma care. Conclusions: We have reviewed some special considerations needed to address the complexity of providing guideline-concordant glaucoma care.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.526
Threshold uncertainty score0.571

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 integrity0.0000.000
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 head0.082
GPT teacher head0.378
Teacher spread0.296 · 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