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Record W3083446900 · doi:10.1097/ruq.0000000000000514

Contrast -Enhanced Ultrasound

2020· review· en· W3083446900 on OpenAlexaff
R. Graham Barr, Stephanie R. Wilson, Andrej Lyshchik, Beth McCarville, Kassa Darge, Edward G. Grant, Michelle L. Robbin, Juergen Karl Wilmann, Wui K. Chong, Arthur C. Fleischer, Harriet J. Paltiel

Bibliographic record

VenueUltrasound Quarterly · 2020
Typereview
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineContrast (vision)Contrast-enhanced ultrasoundUltrasoundMedical physicsRadiologyArtificial intelligence

Abstract

fetched live from OpenAlex

The Society of Radiologists in Ultrasound convened a panel of specialists in contrast-enhanced ultrasound (CEUS) to produce a white paper on noncardiac CEUS in North America. The panel met in Chicago, Illinois, on October 24 and 25, 2017. The recommendations are based on analysis of current literature and common practice strategies and are thought to represent a reasonable approach to introduce the advantages of this safe and noninvasive technique for the benefit of our patients. Characterization of liver nodules, and pediatric vascular and intravesicular applications comprise the approved indications for CEUS in the United States. They, along with the very successful off-label use of CEUS for the kidney, are included in this publication.Other off-label uses are presented with emphasis on their value and literature support in the online version.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.004

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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2020
Admission routes1
Has abstractyes

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