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Record W2166062026 · doi:10.1586/era.10.24

CT and MRI of hepatocellular carcinoma: an update

2010· review· en· W2166062026 on OpenAlex
Anoop Ayyappan, Kartik Jhaveri

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

VenueExpert Review of Anticancer Therapy · 2010
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsMedicineHypervascularityHepatocellular carcinomaRadiologyMagnetic resonance imagingCirrhosisBiopsyInternal medicine

Abstract

fetched live from OpenAlex

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide and one of the few malignancies with an increasing incidence in the USA. Imaging plays a crucial role in early detection, accurate staging and planning management strategies. Contrast material-enhanced MRI or computed tomography (CT) are the best imaging techniques currently available for the noninvasive diagnosis of HCC. The diagnosis of HCC is strongly dependent on hemodynamic features (arterial hypervascularity and washout in the venous phase) on dynamic imaging, and biopsy is no longer recommended for tumors with classical imaging features prior to treatment. The major challenge for radiologists in imaging cirrhosis is the characterization of hypervascular nodules smaller than 2 cm, which often have nonspecific imaging characteristics. In this review, we discuss the role of CT and MRI in the diagnosis and staging of HCC. The strengths and current limitations of these imaging modalities are highlighted.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
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)0.0010.000

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 head0.082
GPT teacher head0.359
Teacher spread0.278 · 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