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Record W1995900860 · doi:10.1159/000333261

Controversies in Surveillance and Early Diagnosis of Hepatocellular Carcinoma

2011· article· en· W1995900860 on OpenAlexaff
Do Young Kim, Jin‐Wook Kim, Ryoko Kuromatsu, Sang Hoon Ahn, Takuji Torimura, Morris Sherman

Bibliographic record

VenueOncology · 2011
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsHepatocellular carcinomaMedicineBiomarkerCancerCarcinomaOncologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

The surveillance of hepatocellular carcinoma (HCC) is an established approach to detect early cancers in patients with defined risks. However, there are still varied controversies and issues to be addressed regarding the optimal surveillance methods and interval. Moreover, there are discrepancies in the opinion or practice of HCC surveillance between Eastern and Western countries. The Western strategy of ultrasound without a biomarker such as α-fetoprotein reflects the cost-effective utilization of limited resources. On the contrary, combined measurements of biomarkers in Eastern countries are based on the assumption that increased detection of early cancers could result in an overall survival benefit. To address this complicated issue, a prospective study comparing different surveillance tests might be required. More importantly, discovery of a novel biomarker with higher performance would be an alternative.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.093
metaresearch head score (Gemma)0.190
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.093
Threshold uncertainty score0.490

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0930.190
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0020.010
Scholarly communication0.0050.010
Open science0.0040.004
Research integrity0.0090.014
Insufficient payload (model declined to judge)0.0020.001

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 head0.068
GPT teacher head0.255
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations20
Published2011
Admission routes1
Has abstractyes

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