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Record W2059763304 · doi:10.1167/iovs.14-16049

Advancing Therapeutic Strategies for Inherited Retinal Degeneration: Recommendations From the Monaciano Symposium

2015· review· en· W2059763304 on OpenAlexafffund
Debra A. Thompson, Robin R. Ali, Eyal Banin, Kari Branham, John G. Flannery, David M. Gamm, William W. Hauswirth, John R. Heckenlively, Alessandro Iannaccone, Thiran Jayasundera, Naheed W. Khan, Robert S. Molday, Mark E. Pennesi, Thomas A. Reh, Richard G. Weleber, David N. Zacks

Bibliographic record

VenueInvestigative Ophthalmology & Visual Science · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity of British Columbia
FundersInstitute of GeneticsNational Eye InstituteCollege of Engineering, Michigan State UniversityMedical School, University of MichiganHospital for Sick ChildrenMoorfields Eye Hospital NHS Foundation TrustCentre National de la Recherche ScientifiqueUniversiteit GentHebrew University of JerusalemNational Institute of General Medical SciencesNational Institute for Health and Care ResearchStrongMichigan State UniversityChildren's Hospital of PhiladelphiaInstitut National de la Santé et de la Recherche MédicaleUniversity of MichiganMedical Research CouncilHealth Science Center, University of TennesseeUniversitair Ziekenhuis GentUniversity of Wisconsin-MadisonUniversity of WashingtonResearch to Prevent Blindness
KeywordsBlindingPosition paperBench to bedsideRetinal degenerationNeuroscienceMedicineEngineering ethicsPolitical scienceRetinalPsychologyOphthalmologyClinical trialEngineeringPathologyMedical physics

Abstract

fetched live from OpenAlex

Although rare in the general population, retinal dystrophies occupy a central position in current efforts to develop innovative therapies for blinding diseases. This status derives, in part, from the unique biology, accessibility, and function of the retina, as well as from the synergy between molecular discoveries and transformative advances in functional assessment and retinal imaging. The combination of these factors has fueled remarkable progress in the field, while at the same time creating complex challenges for organizing collective efforts aimed at advancing translational research. The present position paper outlines recent progress in gene therapy and cell therapy for this group of disorders, and presents a set of recommendations for addressing the challenges remaining for the coming decade. It is hoped that the formulation of these recommendations will stimulate discussions among researchers, funding agencies, industry, and policy makers that will accelerate the development of safe and effective treatments for retinal dystrophies and related diseases.

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)0.005
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0020.002
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.004

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 head0.076
GPT teacher head0.391
Teacher spread0.315 · 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

Citations97
Published2015
Admission routes2
Has abstractyes

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