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Record W3033768866 · doi:10.1148/radiol.2020192437

Update to the Society of Radiologists in Ultrasound Liver Elastography Consensus Statement

2020· review· en· W3033768866 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

VenueRadiology · 2020
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineElastographyUltrasoundRadiologyMedical physics

Abstract

fetched live from OpenAlex

This multidisciplinary update of the Society of Radiologists in Ultrasound consensus statement on liver elastography incorporates the large volume of new information available in the literature since the initial publication. The recommended procedure for acquiring stiffness measurements is reviewed. There has been substantial improvement in the acoustic radiation force impulse (ARFI) technology-most notably the addition of a quality assessment of the shear wave propagation. Due to the efforts of the Quantitative Imaging Biomarkers Alliance, or QIBA, the variability of liver stiffness measurements between systems had decreased. There are now effective treatments for hepatitis B and hepatitis C, and follow-up after effective treatment should be based on the use of the delta change of the value obtained at viral eradication or suppression. Because the detection of compensated advanced chronic liver disease (cACLD) is very important, the new guidelines are made based on the probability of cACLD for given stiffness values. The panel recommends a vendor-neutral rule of four for interpretation for ARFI techniques. This new method simplifies interpretation of liver stiffness results and is more clinically relevant.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.762
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
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 head0.045
GPT teacher head0.336
Teacher spread0.290 · 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