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Record W1511870879 · doi:10.1159/000322429

Image Guidance and the New Practice of Radiotherapy: What to Know and Use from a Decade of Investigation

2011· review· en· W1511870879 on OpenAlexaff
John Kim, John L. Meyer, Laura A. Dawson

Bibliographic record

VenueFrontiers of radiation therapy and oncology · 2011
Typereview
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsImage-guided radiation therapyMedicineMedical physicsLimitingRadiation therapyExploitMedical imagingRadiologyComputer scienceEngineering

Abstract

fetched live from OpenAlex

Over the past decade, fundamental advances in image-guided radiation therapy (IGRT) have been made that are now being implemented in clinical practice. Imaging technologies to direct and confirm beam accuracy at the time of radiotherapy delivery have been intensively researched and developed. More recently, these imaging data have been used to evaluate and even modify the daily dose delivery of intended treatment plans. The rationale for the use of IGRT, to improve tumor control while limiting normal tissue toxicity, is a universal goal in radiotherapy. Avoidance of unexpected under- or overdosing during treatment is the most important benefit of IGRT, and has led to its integration into the use of advanced radiotherapy planning/delivery technologies for many clinical applications. Evidence-based strategies to effectively use IGRT in the clinic are still emerging. The evolving role of IGRT and some proposed strategies to exploit its potential benefits in the clinic will be presented, emphasizing the perspective of the radiation clinician. Practical strategies will be proposed to exploit the potential benefits of IGRT technologies in the clinic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.991
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.324
Teacher spread0.303 · 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 teacher head, 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

Citations7
Published2011
Admission routes1
Has abstractyes

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