MétaCan
Menu
Back to cohort
Record W1964286914 · doi:10.1364/josaa.23.000483

Computational studies of optical textures of twist disclination loops in liquid-crystal films by using the finite-difference time-domain method

2006· article· en· W1964286914 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

VenueJournal of the Optical Society of America A · 2006
Typearticle
Languageen
FieldEngineering
TopicOptical Polarization and Ellipsometry
Canadian institutionsMcGill University
Fundersnot available
KeywordsDisclinationFinite-difference time-domain methodPolarizerOpticsLiquid crystalMaterials scienceMatrix methodTwistPlanarTexture (cosmology)Matrix (chemical analysis)PhysicsComputer scienceGeometryMathematicsImage (mathematics)

Abstract

fetched live from OpenAlex

Optical images of textured liquid-crystal films containing various types of twist disclination loops are computed using an approximate matrix method and a direct numerical simulation based on the finite-difference time-domain (FDTD) method. The selected defects introduce large multidirectional spatial gradients in the optic axis, mimicking the orientation textures that arise in the construction and use of biosensors based on liquid-crystal vision. It is shown that under these experimentally relevant conditions, the matrix method fails to capture important signatures in the transmitted light intensity under crossed polarizers. The differences between the predictions by the two methods are analyzed with respect to gradients in the optic axis. We show that the FDTD method is a useful tool to perform computational optics of textured liquid-crystal films.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.386
Threshold uncertainty score0.314

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 studies0.0000.001
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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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