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Record W4389344985 · doi:10.2147/opth.s450993

Novel Technique to Improve the Efficacy of Corneal Cross Linking in Cases of Post LASIK Ectasia [Letter]

2023· article· en· W4389344985 on OpenAlexaffabout
Avi Wallerstein, Adam Michael Wandzura, Mathieu Gauvin

Bibliographic record

VenueClinical ophthalmology · 2023
Typearticle
Languageen
FieldMedicine
TopicCorneal surgery and disorders
Canadian institutionsUniversity of SaskatchewanMcGill University
Fundersnot available
KeywordsMedicineLASIKOphthalmologyEctasiaOptometrySurgery

Abstract

fetched live from OpenAlex

Avi Wallerstein,1,2,* Adam Wandzura,3,* Mathieu Gauvin1,2,* 1Department of Ophthalmology and Visual Sciences, McGill University, Montreal, QC, Canada; 2LASIK MD, Montreal, QC, Canada; 3University of Saskatchewan, College of Medicine, Saskatoon, SK, Canada*These authors contributed equally to this workCorrespondence: Avi Wallerstein, Tel +1 514-908-9888 Ext 2273, Email awallerstein@lasikmd.com

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.088
GPT teacher head0.426
Teacher spread0.338 · 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 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

Citations1
Published2023
Admission routes2
Has abstractyes

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