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Record W6891505227 · doi:10.3886/e117543

The Foveal Avascular Zone Image Database (FAZID)

2020· dataset· en· W6891505227 on OpenAlexaff

Bibliographic record

VenueICPSR Data Holdings · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFoveal avascular zoneFovealFundus (uterus)PixelSegmentationRetinalFeature (linguistics)

Abstract

fetched live from OpenAlex

The Foveal Avascular Zone (FAZ) is of clinical importance since the vascular arrangement around the fovea changes with disease and refractive state of the eye. In order to test and validate newly developed automated segmentation algorithms, we have created a public dataset of these retinal fundus images consisting of a total of 304 different images classified into: Diabetic (107), Myopic (109) and Normal (88) eyes. The images are of dimensions 420 x 420 pixels corresponding to 6mm x 6mm dimension of the retina. For each type of image, clear and manually segmented by a clinical expert (ground truth) are available.<br><br>Please use the following citation if you use the database “Jothi Balaji, J.; Agarwal, A.; Raman, R., et al., Comparison of Foveal Avascular Zone in Diabetic Retinopathy, High Myopia and Normal Fundus images. Ophthalmic Technologies XXX, Vol 11218-59. Proc. SPIE (2020).” (To be appeared)

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.124
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0180.017
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.125

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 head0.050
GPT teacher head0.306
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueICPSR Data HoldingsFrench-language works237,207