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Record W1995225119 · doi:10.2349/biij.3.1.e16

Tomotherapy as a tool in image-guided radiation therapy (IGRT): theoretical and technological aspects

2007· article· en· W1995225119 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomedical Imaging and Intervention Journal · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsLondon Health Sciences Centre
FundersGovernment of OntarioOntario Institute for Cancer Research
KeywordsTomotherapyMultileaf collimatorImage-guided radiation therapyLinear particle acceleratorCollimated lightContext (archaeology)CollimatorMedical physicsNuclear medicineRadiosurgeryBeam (structure)Radiation therapyComputer scienceMedical imagingOpticsMedicinePhysicsArtificial intelligenceRadiologyLaser

Abstract

fetched live from OpenAlex

Helical tomotherapy (HT) is a novel treatment approach that combines Intensity-Modulate Radiation Therapy (IMRT) delivery with in-built image guidance using megavoltage (MV) CT scanning. The technique utilises a 6 MV linear accelerator mounted on a CT type ring gantry. The beam is collimated to a fan beam, which is intensity modulated using a binary multileaf collimator (MLC). As the patient advances slowly through the ring gantry, the linac rotates around the patient with a leaf-opening pattern optimised to deliver a highly conformal dose distribution to the target in the helical beam trajectory. The unit also allows the acquisition of MVCT images using the same radiation source detuned to reduce its effective energy to 3.5 MV, making the dose required for imaging less than 3 cGy. This paper discusses the major features of HT and describes the advantages and disadvantages of this approach in the context of the commercial Hi-ART system.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.915
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.317
Teacher spread0.311 · 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