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Record W3085055056 · doi:10.1002/ajmg.c.31834

A diagnostic approach to syndromic retinal dystrophies with intellectual disability

2020· review· en· W3085055056 on OpenAlexaff
Xiao‐Ru Yang, Matthew D. Benson, Ian M. MacDonald, A. Micheil Innes

Bibliographic record

VenueAmerican Journal of Medical Genetics Part C Seminars in Medical Genetics · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsIntellectual disabilityRetinal DisorderMedicineDystrophyDiseaseStargardt diseaseDifferential diagnosisRetinalPediatricsPathologyOphthalmologyPsychiatry

Abstract

fetched live from OpenAlex

Inherited retinal dystrophies are a group of monogenic disorders that, as a whole, contribute significantly to the burden of ocular disease in both pediatric and adult patients. In their syndromic forms, retinal dystrophies can be observed in association with intellectual disability, frequently alongside other systemic manifestations. There are now over 80 genes implicated in syndromic retinal dystrophies with intellectual disability. Identifying and accurately characterizing these disorders allows the clinician to narrow the differential diagnosis, evaluate for relevant associated features, arrive at a timely and accurate diagnosis, and address both sight-threatening ocular manifestations and morbidity-causing systemic manifestations. The co-occurrence of retinal dystrophy and intellectual disability in an individual can be challenging to investigate, diagnose, and counsel given the considerable phenotypic and genotypic heterogeneity that exists within this broad group of disorders. We performed a review of the current literature and propose an algorithm to facilitate the evaluation, and clinical and mechanistic classification, of these individuals.

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)0.002
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
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 head0.016
GPT teacher head0.307
Teacher spread0.290 · 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.

Study designOther design
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

Citations11
Published2020
Admission routes1
Has abstractyes

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