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Record W1525969521 · doi:10.1159/000106031

Kilovoltage Volumetric Imaging in the Treatment Room

2007· review· en· W1525969521 on OpenAlexaff
David A. Jaffray

Bibliographic record

VenueFrontiers of radiation therapy and oncology · 2007
Typereview
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsOntario Institute for Cancer Research
Fundersnot available
KeywordsTomotherapyCone beam ctComputer scienceModality (human–computer interaction)WorkloadMedical physicsRadiation therapyMedicineRadiologyArtificial intelligenceComputed tomography

Abstract

fetched live from OpenAlex

Flat-panel cone beam CT is maturing to a stable imaging modality. Applications are being developed for radiotherapy, volumetric diagnostic scanning, rotational angiography and mobile C-arm technologies with soft tissue imaging capabilities. Volumetric image-guided radiotherapy is technologically feasible, and has been proven clinically useful with cone beam CT, CT on rails and tomotherapy design configurations. Soft-tissue-based guidance of field placement is now possible for many sites. Evaluation of the relative merits of these technologies requires that the objective of imaging be well defined. Relevant questions include: Can the target or normal structure of interest be localized with the desired precision and accuracy? Can the patient's position be adjusted based on this information within the time constraints of the clinical workload? We must be prepared to compromise diverse clinical objectives and technical features in order to achieve systems with defined and useful functionality. These imaging technologies will lead to a better understanding of the weaknesses, and provide opportunity to reduce errors and improve technical execution of radiotherapy delivery.

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 score0.996
Threshold uncertainty score0.742

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.029
GPT teacher head0.353
Teacher spread0.324 · 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

Citations24
Published2007
Admission routes1
Has abstractyes

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