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Record W2029127061 · doi:10.1167/iovs.10-6905

Properties of the Statpac Visual Field Index

2011· article· en· W2029127061 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

VenueInvestigative Ophthalmology & Visual Science · 2011
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsDalhousie University
Fundersnot available
KeywordsVisual fieldGlaucomaAbsolute deviationOphthalmologyStatistical significanceMathematicsMedicineVisual field testLinear regressionCeiling effectOptometryStatisticsAudiology

Abstract

fetched live from OpenAlex

Purpose. To compare the properties of the visual field index (VFI) to those of mean deviation (MD) in patients with glaucoma. Methods. MD and VFI were calculated in data obtained from an ongoing longitudinal study in which patients with glaucoma (N = 109, 204 eyes) were observed for 9.8 years (median, 21 tests) with static automated perimetry. MD and VFI were compared in one test of each eye, and a subset of 30 tests were selected to compare the VFI with the judgments of eight experts who judged the percentage of the remaining visual field. In series of tests obtained over time, rates of change, statistical significance, evidence of nonlinearity, and variability were compared between both indices. Results. In single tests, MD and VFI were closely related (r = 0.88, P < 0.001). The relationship between both indices appeared linear, except in visual fields with MDs better than -5.0 dB where 29 (22%) of 129 eyes exhibited a ceiling effect (VFI = 100%). Based on this relationship, the predicted VFIs for visual fields with MDs of -5, -10, and -15 dB were 91%, 76%, and 60%, respectively. The percentage of remaining visual field suggested by the VFI exceeded the range of the experts' subjective judgments in 16 (53%) of 30 eyes. In series of tests obtained over time, rates of change with the two indices were closely related (r = 0.79, P < 0.001), and statistically significant reductions over time (P < 0.05) occurred in a similar number of eyes (92 [45%] with MD, and 87 [43%] with VFI). Of the 105 eyes with statistically significant (P < 0.05) negative trend in either MD or VFI, 74 (70%) showed such trends with both indices (κ = 0.69). The variability of MD and VFI increased with damage, and there was no evidence that change over time was more linear with VFI than with MD. Conclusions. The VFI provides a simple and understandable metric of visual field damage, but its estimates of remaining visual field were more optimistic than those of the experts. Rates of change over time with both indices were closely related, but the reliance of the VFI on pattern deviation probability maps caused a ceiling effect that may have reduced its sensitivity to change in eyes with early damage. In this group of patients there was no evidence to suggest that the VFI is either superior or inferior to the MD as a summary measure of visual field damage.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.007
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 head0.056
GPT teacher head0.322
Teacher spread0.266 · 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