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Record W2170576687 · doi:10.4021/gr2009.10.1314

Approach to Solid Liver Masses in the Cirrhotic Patient

2009· review· en· W2170576687 on OpenAlexvenueno aff
Nimer Assy

Bibliographic record

VenueGastroenterology Research · 2009
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiochemistryChemistry

Abstract

fetched live from OpenAlex

Liver masses in cirrhosis are increasingly being recognized with the use of new imaging modalities. The majority of these lesions are detected by ultrasound, enhanced CT and MRI. The most likely diagnosis of a solid liver lesion in a cirrhotic liver is hepatocellular carcinoma, followed by high grade or low grade dysplastic nodule, and cholangiocarcinoma. Lymphoma and liver metastasis are extremely rare. Diagnosis is made by contrast enhanced ultrasound, multi detector (MDCT) and MRI. Fine needle core biopsy (FNCB) or aspiration (FNAB) or both may be required in doubtful cases. If uncertainty persists on the nature of the lesion, surgical liver resection is recommended. This review discusses the main characteristics of the most common solid liver masses in cirrhotic patient.

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)0.000
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 score0.973
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.345
GPT teacher head0.418
Teacher spread0.074 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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