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Record W2251775735 · doi:10.1016/j.carj.2015.07.005

Approach to the Solitary Liver Lesion: Imaging and When to Biopsy

2015· review· en· W2251775735 on OpenAlexaff
Emily Pang, Alison Harris, Silvia D. Chang

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2015
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineRadiologyBiopsyMagnetic resonance imagingContrast-enhanced ultrasoundLiver biopsyLesionFine-needle aspirationUltrasoundCore biopsyPathologyCancerInternal medicine

Abstract

fetched live from OpenAlex

The characterization and management of focal liver lesions is a commonly encountered problem in radiology. While the imaging findings will often be diagnostic, in equivocal cases the decision of how to proceed may be challenging. The primary modalities for liver lesion characterization are multiphase contrast-enhanced computed tomography and magnetic resonance imaging. Most lesions have typical imaging features, and when taken in conjunction with patient demographics and biochemistry the diagnosis can usually be made. Ancillary imaging modalities such as contrast-enhanced ultrasound and hepatobiliary specific contrast agents are also useful. Cirrhotic livers present a challenge due to the spectrum of benign, dysplastic, and malignant nodules that can occur. The report should include information necessary for accurate staging, and published standardized reporting guidelines should be taken into consideration. A decision to proceed to biopsy should be made only after multidisciplinary review of the case. If biopsy is required, fine needle aspiration is usually sufficient, though core needle biopsy may be required in certain circumstances.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.746
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.139
GPT teacher head0.305
Teacher spread0.165 · 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
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

Citations17
Published2015
Admission routes1
Has abstractyes

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