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Optic Nerve Measurements by 3D Ultrasound-Based Coronal "C-scan" Imaging

2005· article· en· W102406849 on OpenAlexaboutno aff
J.P. S. Garcia, Patricia Garcia, Richard B. Rosen, Paul T. Finger

Bibliographic record

VenueOphthalmic surgery, lasers & imaging retina · 2005
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsCoronal planeUltrasoundMedicineOptic nerveUltrasound imaging3D ultrasoundRadiologyOphthalmology

Abstract

fetched live from OpenAlex

Twenty-three normal eyes were examined with the Intensity Profiling technique of 3D I-Scan and 52 normal eyes with the Automated technique of OTI-Scan 1000 ultrasound systems (Ophthalmic Technologies Inc., Toronto, Ontario, Canada). With the eye looking straight, the probe was applied on the temporal sclera. Scanning generated 3D image files. Coronal optic nerve measurements were obtained 3 mm behind the globe. The mean optic nerve sheath diameter was 4.8 mm (standard deviation = 0.6; range, 3.9 to 5.9 mm) with the Intensity Profiling technique, and 5.4 mm (standard deviation = 0.4; range, 4.4 to 6.0 mm) with the Automated technique. 3D ultrasound imaging can be used to obtain optic nerve measurements in vivo. Both the Intensity Profiling and the Automated techniques yielded measurements similar to current magnetic resonance imaging and computed tomography scan reports. Coronal "C-scan" sectioning can be used as a screening tool to measure optic nerve diameter prior to magnetic resonance imaging or computed tomography.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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 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

Citations30
Published2005
Admission routes1
Has abstractyes

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