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The Repeatability of Discrete and Continuous Anterior Segment Grading Scales

2000· article· en· W1982709658 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOptometry and Vision Science · 2000
Typearticle
Languageen
FieldMedicine
TopicOcular Surface and Contact Lens
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsRepeatabilityIntraclass correlationGrading scaleGrading (engineering)ConcordanceReproducibilityPalpebral fissureCorrelation coefficientMathematicsPearson product-moment correlation coefficientMedicineOphthalmologyStatisticsSurgery

Abstract

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PURPOSE: To investigate the repeatability of three anterior segment clinical grading scales: 1) verbal descriptors scale (VDS), 2) photographic matching scale (PS), and 3) continuous matching scale (CS). METHODS: Five optometrists graded 30 slides each of 3-9-o'clock staining, bulbar redness, and palpebral conjunctival roughness twice, separated by at least a day. VDS and PS were five-point scales (0-4) with half grades permitted. The CS was a 5-second, 240-frame video movie generated using morphing software. PS and CS grading was done with references presented on a computer screen. RESULTS: Averaged across observers, the test-retest intraclass correlation, correlation coefficient of concordance, and Pearson's r ranged from 0.95 to 0.99 (all p < 0.001). Coefficients of repeatability using CS to grade all three ocular conditions ranged between 0.31 and 0.49. The corresponding PS and VDS coefficients of repeatability ranged between 0.37 and 0.49; PS generally had better repeatability than VDS. CONCLUSIONS: Each of the clinical grading scales was reliable. The coefficients of repeatability showed that bulbar redness and palpebral conjunctival roughness were graded with higher precision using CS.

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.

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)0.000
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 score0.382
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.008
GPT teacher head0.370
Teacher spread0.362 · 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