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Record W2024703231 · doi:10.1097/aln.0b013e318272d78b

Ultrasound Investigation and the Eye

2012· letter· en· W2024703231 on OpenAlexaboutno aff
Howard D. Palte, Steven Gayer

Bibliographic record

VenueAnesthesiology · 2012
Typeletter
Languageen
FieldMedicine
TopicNeurological Complications and Syndromes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineUltrasoundOptometryMedical physicsOphthalmologyRadiology

Abstract

fetched live from OpenAlex

We read with interest the elegant article by Dubost et al. 1documenting a correlation between increased optic nerve sheath diameters and preeclampsia. At Bascom Palmer Eye Institute we have been studying the potential application of sonography for ophthalmic regional anesthesia.The application of sonic energy around the eye is not without risk. Thermal and mechanical bio-effects are well described. Multiple international regulatory authorities, including the U.S. Food and Drug Administration2and Health Canada* have imposed stricter physical parameters for the use of ophthalmic ultrasound. In particular, limits on Mechanical Index and Thermal Index have been reduced to 0.23 and less than 1, respectively.We recently published a rabbit model study that compared thermal and mechanical changes induced by exposure to ophthalmic- and nonophthalmic-rated transducers.3Our data showed significant changes in intraorbital temperature after exposure to the nonorbital rated Sonosite Micromaxx 6-13 MHz linear transducer (Bothell, WA).Great benefit may emanate from intra- or perioperative ultrasonic ocular examinations, whether for optic nerve sheath diameters, regional anesthesia, or other applications. Investigators must remain cognizant of the potential deleterious ocular effects of sonic energy, and ensure that only orbital-approved technology is used in future research.†University of Miami, Miller School of Medicine, Miami, Florida. hpalte@med.miami.edu

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 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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.219
Threshold uncertainty score0.372

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 integrity0.0000.001
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 head0.035
GPT teacher head0.263
Teacher spread0.228 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations19
Published2012
Admission routes1
Has abstractyes

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