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Clinical trials for inherited optic neuropathies

2017· article· en· W2752426219 on OpenAlexaff
Rustum Karanjia, Lissa Poincenot, Alfredo A. Sadun

Bibliographic record

VenueActa Ophthalmologica · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineClinical trialOptometryOphthalmologyInternal medicine

Abstract

fetched live from OpenAlex

Summary The best scientific evidence for use of a clinical intervention is based upon data obtained from Phase III clinical trials. The robustness of a clinical trial is dependent on the quality of the metrics collected which in turn is dependent on the design of the study. Clinical trials involving inherited optic neuropathies such as Leber's Hereditary Optic Neuropathy ( LHON ) encounter some unique challenges which can be divided into two broad groups: patient‐centric factors and test‐centric factors. Patient‐centric factors include the heterogeneous phenotypic presentations in LHON with variable rates of spontaneous recovery and time to nadir and plateau. Test‐centric factors include the subjective nature of most visual metrics; intertest and intratest variability, which is compounded by patient adaptation to visual loss. Collectively these issues must be addressed when designing a clinical trial, especially in rare diseases where patient recruitment can be a challenge

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)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.016
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 head0.225
GPT teacher head0.433
Teacher spread0.207 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2017
Admission routes1
Has abstractyes

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