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Record W3026880214 · doi:10.1080/13816810.2020.1766087

<i>KCNV2</i> retinopathy: clinical features, molecular genetics and directions for future therapy

2020· review· en· W3026880214 on OpenAlexfundno aff
Thales A. C. de Guimarães, Michalis Georgiou, Anthony G. Robson, Michel Michaelides

Bibliographic record

VenueOphthalmic Genetics · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsnot available
FundersNational Institute for Health Research Biomedical Research Centre at Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of OphthalmologyFoundation Fighting BlindnessFight for Sight UKRetina UKWellcome TrustWellcome
KeywordsGeneticsMolecular geneticsMedicineOphthalmologyBiologyBioinformaticsGene

Abstract

fetched live from OpenAlex

KCNV2 -associated retinopathy or “cone dystrophy with supernormal rod responses” is an autosomal recessive cone-rod dystrophy with pathognomonic ERG findings. This gene encodes Kv8.2, a voltage-gated potassium channel subunit that acts as a modulator by shifting the activation range of the K+ channels in photoreceptor inner segments. Currently, no treatment is available for the condition. However, there is a lack of prospective long-term data in large molecularly confirmed cohorts, which is a prerequisite for accurate patient counselling/prognostication, to identify an optimal window for intervention and outcome measures, and ultimately to design future therapy trials. Herein we provide a detailed review of the clinical features, retinal imaging, electrophysiology and psychophysical studies, molecular genetics, and briefly discuss future prospects for therapy trials.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.004

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 head0.038
GPT teacher head0.360
Teacher spread0.322 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations37
Published2020
Admission routes1
Has abstractyes

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