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Record W2326989721 · doi:10.1097/opx.0000000000000583

Comparison of Matrix with Humphrey Field Analyzer II with SITA

2015· article· en· W2326989721 on OpenAlexafffund
Marie-Josée Fredette, Anik Giguère, Douglas R. Anderson, Donald L. Budenz, John McSoley

Bibliographic record

VenueOptometry and Vision Science · 2015
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
FundersUniversité Laval
KeywordsStandard deviationRepeatabilityIntraclass correlationDecibelMathematicsStatisticsAbsolute deviationSpectrum analyzerSensitivity (control systems)Coefficient of variationMatrix (chemical analysis)MedicineReproducibilityOpticsAudiologyMaterials sciencePhysics

Abstract

fetched live from OpenAlex

PURPOSE: To study the performance of the Matrix perimeter compared with the Humphrey Field Analyzer II (HFA) with the Swedish Interactive Thresholding Algorithm over the range of contrast sensitivities each machine could estimate. METHODS: Fifty stable glaucoma subjects at various stages of disease and three normal subjects had visual fields testing done on five different days within 8 weeks with both perimeters. Intraclass correlation coefficient of mean deviation, pattern standard deviation, and the SD of repeat measurements were evaluated. The repeatability of the sensitivity estimates at individual locations and global indices was quantified, as well as their dependence on disease severity. The relationship between sensitivity determinations with the two instruments was explored (principal curve analysis). RESULTS: Mean deviation on the HFA ranged from -31 to +2.5 dB. The mean deviation and pattern standard deviation had intraclass correlation coefficients above 0.90 for both instruments. Over most of the useful range (above 20 dB on the HFA), a difference of 1 dB for the Matrix corresponded to a difference of 2 dB for the HFA. The SD of repeat measurements increased with disease severity with HFA, but not with Matrix, except that values of 12 or 34 dB were highly variable on repeat. Variability was reduced for both HFA and Matrix when duplicate sensitivity values were used. A single Matrix test provided only 15 possible sensitivity values, unevenly spaced, but the average of duplicate measurements provided more numerous sensitivity values. A learning effect was detected for Matrix. CONCLUSIONS: The decibel values reported by the two machines are not equivalent. Variability of sensitivity determinations is affected more by the sensitivity level with HFA than with Matrix. Duplicate measurements for baseline and follow-up evaluation could be important, especially for Matrix. Further information on learning effects is needed, as is commercially available progression software for Matrix.

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)0.003
metaresearch head score (Gemma)0.012
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.448
Teacher spread0.427 · 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

Citations18
Published2015
Admission routes2
Has abstractyes

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