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Record W1940218692 · doi:10.2217/fon.15.220

The Development of Stereotactic Body Radiotherapy in the Past Decade: A Global Perspective

2015· article· en· W1940218692 on OpenAlexaffabout
Simon S. Lo, Ben J. Slotman, Michael Lock, Yasushi Nagata, Matthias Gückenberger, Shankar Siva, Matthew Foote, Daniel S.W. Tan, Bin S. Teh, Nina A. Mayr, Eric L. Chang, Robert Timmerman, Arjun Sahgal

Bibliographic record

VenueFuture Oncology · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of TorontoSunnybrook Health Science CentreWestern University
Fundersnot available
KeywordsMedicineStereotactic radiotherapyRadiation therapyRadiation oncologyPerspective (graphical)Ablative caseRadiosurgeryMedical physicsInternal medicine

Abstract

fetched live from OpenAlex

In the past 10 years, there has been an exponential increase in the incorporation of stereotactic body radiotherapy, also known as stereotactic ablative radiotherapy, into the armamentarium against various types of cancer in different settings worldwide. In this article in the 10th year anniversary issue of Future Oncology, representatives from the USA, Canada, Japan, Germany, The Netherlands, Australia and Singapore will provide individual perspectives of the development of stereotactic body radiotherapy in their respective countries.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.016
GPT teacher head0.350
Teacher spread0.334 · 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

Citations10
Published2015
Admission routes2
Has abstractyes

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