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Record W1556014687 · doi:10.1159/000323355

Advanced Technologies in the Radiotherapy Clinic: System Fundamentals

2011· review· en· W1556014687 on OpenAlexaff
John L. Meyer, Michael Sharpe, K Brock, Joseph O. Deasy, Tim Craig, D Moseley, J Alaly, Konstatin Zakaryan

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
KeywordsMedical physicsPlan (archaeology)Process (computing)Computer scienceAdaptation (eye)ContouringRadiation treatment planningQuality (philosophy)Systems engineeringProcess managementRisk analysis (engineering)Radiation therapyMedicineEngineeringRadiologyPsychology

Abstract

fetched live from OpenAlex

The radiotherapy treatment process is undergoing rapid development at every step from planning through delivery, and each step is increasingly automated and assisted by new imaging, positioning, contouring and treatment tools. Plan delivery and verification is now aided using an increasing range of image guidance technologies, and imaging at treatment now brings broad opportunities for dose guidance and adaptation for improving overall treatment quality. While these many tools bring exciting opportunities for exact, reliable and efficient targeting of radiation dose, a consistently high level of accuracy must be achieved at every step to achieve the desired results. This level of workmanship requires thorough understanding of the basic methods involved in each step, including the opportunities and limitations, by both the clinicians and the planning/delivery staff alike. These processes and their clinical implementation are discussed in depth throughout this volume. Here, we overview their integration and guiding background concepts, as well as a range of workday efficiencies for clinical practice.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.034
GPT teacher head0.349
Teacher spread0.315 · 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.

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

Citations2
Published2011
Admission routes1
Has abstractyes

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