MétaCan
Menu
Back to cohort
Record W4221076468 · doi:10.1016/j.clon.2022.02.021

Hypofractionation in Hepatocellular Carcinoma – The Effect of Fractionation Size

2022· review· en· W4221076468 on OpenAlexaff
Shirley Lewis, Aisling Barry, M. Hawkins

Bibliographic record

VenueClinical Oncology · 2022
Typereview
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
FundersNational Institute for Health and Care ResearchUniversity College LondonCancer Research UK
KeywordsMedicineHepatocellular carcinomaLimitingRadiation therapyDose fractionationFractionationOncologyIncidence (geometry)CarcinomaInternal medicineRadiologyMedical physics

Abstract

fetched live from OpenAlex

The use of stereotactic body radiotherapy (SBRT) in hepatocellular carcinoma (HCC) has increased over the years. Several prospective studies have demonstrated its safety and efficacy, and randomised trials are underway. The advancement in technology has enabled the transition from three-dimensional conformal radiotherapy to highly focused SBRT. Liver damage is the primary limiting toxicity with radiation, with the incidence of grade 3 varying from 0 to 30%. The reported radiotherapy fractionation schedule for HCC, and in practice use, ranges from one to 10 fractions, based on clinician preference and technology available, tumour location and tumour size. This review summarises the safety and efficacy of various SBRT fractionation schedules for HCC.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.254
GPT teacher head0.446
Teacher spread0.192 · 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
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

Citations20
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueClinical OncologySame topicHepatocellular Carcinoma Treatment and PrognosisFrench-language works237,207