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Record W2790795540 · doi:10.1097/mop.0000000000000026

Advances in the genetics of eye diseases

2013· review· en· W2790795540 on OpenAlexafffund
Stephanie Chan, Paul R. Freund, Ian M. MacDonald

Bibliographic record

VenueCurrent Opinion in Pediatrics · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsAlberta Health ServicesUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsGenetic counselingGenetic testingMedicineDiseaseMedical geneticsGeneticsBioinformaticsGeneBiologyPathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: An update on heritable eye disease will allow informed patient counseling and improved patient care. RECENT FINDINGS: New loci and genes have been associated with identifiable heritable ocular traits. Molecular genetic analysis is available for many of these genes either as part of research or for clinical testing. The advent of gene array technologies has enabled screening of samples for known mutations in genes linked to various disorders. Exomic sequencing has proven to be particularly successful in research protocols in identifying the genetic causation of rare genetic traits by pooling patient resources and discovering new genes. Further, genetic analysis has led improvement in patient care and counselling, as exemplified by the continued advances in our treatment of retinoblastoma. SUMMARY: Patients and families are commonly eager to participate in either research or clinical testing to improve their understanding of the cause and heritability of an ocular condition. Many patients hope that testing will then lead to appropriate treatments or cures. The success of gene therapy in the RPE65 form of Leber congenital amaurosis has provided a brilliant example of this hope; that a similar trial may become available to other patients and families burdened by genetic disease.

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)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.044
GPT teacher head0.384
Teacher spread0.339 · 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 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

Citations8
Published2013
Admission routes2
Has abstractyes

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