MétaCan
Menu
Back to cohort

Optical Coherence Tomography: An Introduction to the Technique and its Use

2000· review· en· W2020432239 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

VenueOptometry and Vision Science · 2000
Typereview
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsOptical coherence tomographyRetinalGlaucomaOptic nerveOpticsCorneaRetinaAdaptive opticsScleraOphthalmologyMedicinePhysics

Abstract

fetched live from OpenAlex

This report describes the new optical imaging technique of optical coherence tomography (OCT). OCT is capable of high-resolution, micrometer-scale, cross-sectional imaging of biological tissue. The OCT for ophthalmic application uses 843-nm, near-infrared light, which produces a longitudinal resolution of 10 to 20 microm and a penetration depth of a few millimeters. The scans are displayed in a false color representation scale on which warm colors represent areas of high optical reflectivity and cool colors represent areas of minimal or no reflectivity. A cross-sectional view similar to a histology section is obtained. The cornea, iris, and lens may be visualized as well as the retina and optic nerve. OCT has been used to investigate several ocular diseases. These include macular disease, genetic retinal disease, retinal detachment and retinoschisis, choroidal tumors, optic nerve disorders, and glaucoma.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
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 head0.041
GPT teacher head0.450
Teacher spread0.409 · 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