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Record W1987659344 · doi:10.2217/fon.14.167

Stereotactic Body Radiotherapy: An Effective Local Treatment Modality for Hepatocellular Carcinoma

2014· review· en· W1987659344 on OpenAlexaff
Jonathan Klein, Renée Korol, Simon S. Lo, William Chu, Michael Lock, Jennifer A. Dorth, Rodney J. Ellis, Nina A. Mayr, Zhibin Huang, Hans T. Chung

Bibliographic record

VenueFuture Oncology · 2014
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversity of TorontoHealth Sciences CentreWestern UniversitySunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineHepatocellular carcinomaRadiation therapyOncologyRadiologyLiver cancerInternal medicine

Abstract

fetched live from OpenAlex

Although liver-directed therapies such as surgery or ablation can cure hepatocellular carcinoma, few patients are eligible due to advanced disease or medical comorbidities. In advanced disease, systemic therapies have yielded only incremental survival benefits. Historically, radiotherapy for liver cancer was dismissed due to concerns over unacceptable toxicities from even moderate doses. Although implementation requires more resources than standard radiotherapy, stereotactic body radiotherapy can deliver reproducible, highly conformal ablative radiotherapy to tumors while minimizing doses to nearby critical structures. Trials of stereotactic body radiotherapy for hepatocellular carcinoma have demonstrated promising local control and survival results with low levels of toxicity in Child-Pugh class A patients. We review the published literature and make recommendations for the future of this emerging modality.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.072
GPT teacher head0.359
Teacher spread0.288 · 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 designSystematic review
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

Citations13
Published2014
Admission routes1
Has abstractyes

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