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Record W2900825720 · doi:10.2147/opth.s178113

A novel scale for describing corneal staining

2018· article· en· W2900825720 on OpenAlexaff
Jill Woods, Jalaiah Varikooty, Desmond Fonn, Lyndon Jones

Bibliographic record

VenueClinical ophthalmology · 2018
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsStainingGrading scaleGrading (engineering)MedicinePositive stainingOphthalmologyScale (ratio)PathologySurgeryCartographyBiology

Abstract

fetched live from OpenAlex

The assessment of corneal staining is a commonly conducted procedure in both clinical practice and as part of various research studies. Different grading scales are employed by many clinicians and researchers to undertake this procedure for corneal staining comparisons between eyes, products and over time. This paper describes the development and use of a grading scale for corneal staining undertaken at an academic research site. The scale involves assessment of three factors across five corneal zones: type, area and depth. Staining type and area are graded on a 0-100 scale, and depth is graded on a 0-4 scale. These factors can be combined to create a three- or two-factor staining grade, or the factors may be reported individually. An additional benefit of this scale is that the staining scores may be reported by zone as "zone staining scores" or the scores of zones may be combined to provide an overall corneal "global staining score".

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)0.008
metaresearch head score (Gemma)0.031
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.031
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.003

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 head0.203
GPT teacher head0.424
Teacher spread0.221 · 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

Citations19
Published2018
Admission routes1
Has abstractyes

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