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Record W2792152477 · doi:10.21037/aes.2018.ab067

AB067. Cholinergic enhancement of short-term patching in healthy adults

2018· article· en· W2792152477 on OpenAlexaff
Yasha Sheynin, Mira Chamoun, Alex Baldwin, Elvire Vaucher, Robert F. Hess

Bibliographic record

VenueAnnals of Eye Science · 2018
Typearticle
Languageen
FieldMedicine
TopicSympathectomy and Hyperhidrosis Treatments
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsTerm (time)CholinergicMedicineInternal medicinePhysics

Abstract

fetched live from OpenAlex

Background: Patching an eye for a period of 2 hours results in a period of plasticity where inter-ocular balance shifts in favor of the patched eye. Acetylcholine has been shown to improve visual function and augment adult neural plasticity. Here we evaluate whether administering the cholinesterase inhibitor donepezil enhances the magnitude or duration of the patching induced shift in ocular balance. Methods: We used a double-blind drug treatment design to test the effect of donepezil and patching on the shift in ocular balance. We used a well-known binocular phase combination task to measure ocular balance before and after treatment. Results: Our results demonstrate that donepezil does not enhance, and may actually reduce the magnitude and duration of the patching-induced shift in ocular balance. Conclusions: Patching induced adult neural plasticity does not appear to be modulated by the cholinergic system, however, increased dose or longer drug administration periods may yield significant results. Future studies on binocular rivalry are in the pipeline.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.066
GPT teacher head0.404
Teacher spread0.337 · 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 designObservational
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
Published2018
Admission routes1
Has abstractyes

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