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Record W2133026324 · doi:10.1017/s0952523804213402

Repeatability indices for the Farnsworth D-15 test

2004· article· en· W2133026324 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueVisual Neuroscience · 2004
Typearticle
Languageen
FieldEngineering
TopicIndustrial Vision Systems and Defect Detection
Canadian institutionsUniversity of Waterloo
FundersTransport Canada
KeywordsRepeatabilityTest (biology)PsychologyBiologyMathematicsStatisticsEcology

Abstract

fetched live from OpenAlex

The repeatability of the D-15 color-vision test is considered to be excellent. However, this conclusion is based on a subject pool which contained a large percentage of color-normals. This type of sampling could bias the repeatability results because color-normals rarely fail the test. Furthermore, color-normals usually do not perform the D-15 in the clinical setting. To establish the repeatability of the D-15 for a relevant clinical population, we examined the D-15 results from two different sessions for 116 subjects who had a congenital red-green color-vision defect. The kappa coefficient for intersession agreement indicated that approximately 84% of the subjects obtained the same pass/fail results at both sessions. The type of defect was repeatable on approximately 80% of the subjects. Although the repeatability of the D-15 for color-defective subjects was good, it was lower than the near-perfect agreement reported previously. The coefficients of repeatability for the crossings show that if a person makes less than five crossings then the test should be administered again in order to ensure that the test result is repeatable.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.287
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.030
GPT teacher head0.286
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