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Record W2623177959 · doi:10.1038/s41598-017-03553-8

The effect of Lasik surgery on myopic anisometropes’ sensory eye dominance

2017· article· en· W2623177959 on OpenAlexafffund
Lixia Feng, Huimin Lin, Yao Chen, Jiafeng Wang, Yonghua Wang, Rongfeng Liao, Jiawei Zhou, Robert F. Hess

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicOphthalmology and Visual Impairment Studies
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of ChinaWenzhou Medical University
KeywordsLASIKOcular dominanceMedicineAnisometropiaSensory systemOphthalmologySurgeryDominance (genetics)Eye diseaseRefractive errorPsychologyBiology

Abstract

fetched live from OpenAlex

Lasik is a common surgery for treating anisometropia. In this study, we asked a specific question: what's the effect of Lasik surgery on anisometropes' sensory eye dominance ? Fifteen myopic anisometropes (mean age: 23 ± 6.9 years old; 6 females) participated in our experiment. We quantitatively measured participants' sensory eye dominance before and after the Lasik surgery using a binocular phase combination paradigm. We found no significant change of sensory eye dominance within 16 weeks (measured between 8 to 96 days, for one or two repetitions) after the surgery (t(14) = -1.44, p = 0.17). A further following on eight patients showed that patients' two eyes were much more balanced at 16 weeks or more (measured one or two times between 112 to 408 days) after the surgery (t(7) = -3.79, p = 0.007). Our results suggest that the benefit of Lasik surgery on anisometropes' sensory eye dominance is not immediate, a long-term 'adaptation' period (16 weeks or more) is necessary to enable the surgery to be truly effective.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.031
GPT teacher head0.359
Teacher spread0.328 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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