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Record W2138447529 · doi:10.1109/iembs.2000.900562

CT imaging for Cobalt-60 helical tomotherapy

2002· article· en· W2138447529 on OpenAlexaff
G Salomons, Gregory A. Gallant, A Kerr, L J Schreiner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsKingston Health Sciences CentreOttawa Regional Cancer Foundation
FundersMedical Research Council
KeywordsTomotherapyContext (archaeology)Medical physicsNuclear medicineModality (human–computer interaction)Materials scienceComputer scienceRadiologyRadiation therapyMedicineArtificial intelligenceGeology

Abstract

fetched live from OpenAlex

Helical tomotherapy, a new technique under development for Intensity Modulated Radiation Therapy, was first proposed by Mackie et al. in 1993. This treatment modality employs a fan-beam radiation source mounted in a CT-like ring gantry, and rotated about the patient. One of the anticipated benefits of helical tomotherapy is the ability to perform in-situ CT imaging to confirm patient set-up, and to reconstruct the dynamically delivered dose distributions. The feasibility of a tomotherapy device using a Cobalt-60 source has previously been demonstrated. Here an investigation of the imaging capabilities of a Co-60 tomotherapy unit is presented. Preliminary results from simulations and measurements on phantoms containing various test objects indicate that megavoltage CT imaging is possible within the context of a Co-60 tomotherapy device.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.013
GPT teacher head0.288
Teacher spread0.275 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2002
Admission routes1
Has abstractyes

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