MétaCan
Menu
Back to cohort
Record W2996204535 · doi:10.1364/josaa.381305

Predicting the Farnsworth–Munsell D15 and Holmes–Wright-A lantern outcomes with computer-based color vision tests

2019· article· en· W2996204535 on OpenAlex
Ali Almustanyir, Jeffery K. Hovis, Mackenzie G. Glaholt

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of the Optical Society of America A · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicReliability and Agreement in Measurement
Canadian institutionsDefence Research and Development CanadaUniversity of Waterloo
FundersCanadian Institute for Military and Veteran Health ResearchDefence Research and Development Canada
KeywordsContrast (vision)WrightMathematicsArtificial intelligenceComputer scienceArtArt history

Abstract

fetched live from OpenAlex

This study determined the AC1 agreement values between computer-based color vision tests and the Farnworth-Munsell D-15 (F-D15) and the Holmes-Wright Type A lantern (HWA). The computer-based tests were the United States Air Force Cone Contrast Test (OCCT), Cambridge Color Test, Innova Rabin Cone Contrast, Konan-Waggoner D15 (KWC-D15), and Color Assessment and Diagnosis (CAD). Sixty-eight color-vision-defective persons participated. The KWC-D15 had the highest AC1 with the F-D15 (${\rm AC1} = {0.88}$AC1=0.88). Both the CAD and OCCT had the highest values with the HWA (${\rm AC1} \gt {0.96}$AC1>0.96). The KWC-D15 would be the best substitute for the F-D15. Either the CAD or OCCT would be appropriate substitutes for the HWA.

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)0.003
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 score0.089
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
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 head0.031
GPT teacher head0.311
Teacher spread0.280 · 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