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Record W2787722663 · doi:10.1155/2018/2734820

Establishing the Role of Stereotactic Ablative Body Radiotherapy in Early-Stage Breast Cancer

2018· review· en· W2787722663 on OpenAlexaff
Aisling Barry, Anthony Fyles

Bibliographic record

VenueInternational Journal of Breast Cancer · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsSABR volatility modelMedicineAblative caseBreast cancerRadiation therapyStage (stratigraphy)CancerMedical physicsRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Stereotactic ablative body radiotherapy (SABR) has a role as definitive therapy in many tumor sites; however, its role in the treatment of breast cancer is less well explored. Currently, SABR has been investigated in the neoadjuvant and adjuvant setting with a number of ongoing feasibility studies. However, its use comes with a number of radiobiological and technical challenges that require further evaluation. We have learned much from other extracranial disease sites such as lung, brain, and spine, where definitive treatment with SABR has shown encouraging outcomes. In women with breast cancer, SABR may eliminate the need for invasive surgery, reducing healthcare costs and hospital stays and providing an additional curative option for early-stage disease. This poses the following question: is there a role for SABR as a definitive therapy in breast cancer?

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)0.002
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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
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 head0.015
GPT teacher head0.337
Teacher spread0.322 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

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