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Record W1995320893 · doi:10.1682/jrrd.2005.02.0040

Recognition distance of pedestrian traffic signals by individuals with low vision

2006· article· en· W1995320893 on OpenAlexaff
Michael Williams, Ron Van Houten, Bruce B. Blasch

Bibliographic record

VenueThe Journal of Rehabilitation Research and Development · 2006
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsIconPedestrianComputer visionAugmented realityLight sourceComputer scienceArtificial intelligenceOpticsEngineeringTransport engineeringPhysics

Abstract

fetched live from OpenAlex

Forty-one individuals with moderate-to-severe vision loss participated in a study to determine the minimum distance they required to correctly identify three different pedestrian traffic icon symbols, one of which was presented with an augmented light source. We found that subjects could identify the WALK icon without the augmented light source information, or animated eyes, from farther away than either the WALK icon with the augmented light source information or the DON'T WALK icon. These results differ from those of a previous study, which found that subjects could correctly identify the WALK icon with the augmented light source from a greater distance than the WALK or DON'T WALK icons without the augmented light source.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.100
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.042
GPT teacher head0.339
Teacher spread0.297 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations3
Published2006
Admission routes1
Has abstractyes

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