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Record W4307379156 · doi:10.1364/josaa.469734

Mathematical modeling and experimental verification of aging human eyes polarization sensitivity

2022· article· en· W4307379156 on OpenAlexaff
Qi Wang, Peter J. Bryanston-Cross, Yahong Li, Zhiying Liu

Bibliographic record

VenueJournal of the Optical Society of America A · 2022
Typearticle
Languageen
FieldEngineering
TopicOptical Polarization and Ellipsometry
Canadian institutionsOptina Diagnostics (Canada)
FundersJilin Scientific and Technological Development ProgramHigher Education Discipline Innovation ProjectChina Scholarship CouncilNational Natural Science Foundation of China
KeywordsPolarization (electrochemistry)PerceptionStokes parametersComputer scienceOptical transfer functionSpatial frequencyOpticsArtificial intelligenceComputer visionPhysicsPsychologyNeuroscience

Abstract

fetched live from OpenAlex

The polarization perception sensitivity of the human eyes affects the perceived polarized image quality. In this paper, we used polarized spatiotemporal structured images to develop a spatiotemporal age mapping of the polarization perception of human eyes. We built an optical modulation transfer function mathematical model of the aging human eyes with spatiotemporal frequency domains and introduced the Stokes vector to analyze the polarized images. The proposed model provides a testing method based on a set of polarization images with spatiotemporal frequencies varying according to the perception of differently aged viewers. Then, we experimentally validated the proposed model by performing polarization perception tests on a group of volunteers. The test method has the diagnostic potential to confirm the health of human eyes and identify potential age-related macular diseases.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations5
Published2022
Admission routes1
Has abstractyes

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Same venueJournal of the Optical Society of America ASame topicOptical Polarization and EllipsometryFrench-language works237,207