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Record W2567056009 · doi:10.1016/j.entcs.2016.12.010

Visual Impairment Simulator Based on the Hadamard Product

2016· article· en· W2567056009 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.

Bibliographic record

VenueElectronic Notes in Theoretical Computer Science · 2016
Typearticle
Languageen
FieldMedicine
TopicRetinal Imaging and Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHeadsetComputer scienceHemianopsiaVisual impairmentComputer visionArtificial intelligenceVirtual realitySet (abstract data type)Hadamard transformReading (process)Task (project management)Face (sociological concept)Computer graphics (images)PsychologyVisual fieldMathematicsEngineering

Abstract

fetched live from OpenAlex

In this paper, a real-time image processing system designed to simulate visual impairment for the normally sighted is presented. The system consists of a video camera, a computer, and a virtual reality (VR) headset. Based on the Hadamard (or Schur) product of the camera's video signal and a set of predefined masks, users can experience eye diseases such as macular degeneration, diabetic retinopathy, glaucoma, hemianopsia, among others. A quantitative user study is presented to illustrate the most complex daily task people with visual impairments face: reading.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.896
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.006
GPT teacher head0.280
Teacher spread0.274 · 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