MétaCan
Menu
Back to cohort
Record W1976647861 · doi:10.1118/1.1308281

Shielding considerations for tomotherapy

2000· article· en· W1976647861 on OpenAlexaff
Don Robinson, John W. Scrimger, G Field, B. G. Fallone

Bibliographic record

VenueMedical Physics · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of VictoriaUniversity of Alberta
Fundersnot available
KeywordsTomotherapyElectromagnetic shieldingShieldRadiation shieldingNuclear engineeringRadiationRadiation protectionLinear particle acceleratorDosimetryMaterials scienceMedical physicsNuclear medicineOpticsPhysicsBeam (structure)Nuclear physicsRadiation therapyEngineeringMedicineRadiologyGeology

Abstract

fetched live from OpenAlex

Tomotherapy presents an evolutionary modality that holds forth the promise of better dose conformation to tumor volumes with a concomitant reduction in radiation-induced damage to surrounding normal structures. This delivery technique also presents a new set of radiation protection challenges that impact upon the design of the shielding vault required to house such a unit. A formalism is presented to determine the requisite amounts of shielding for both the primary beam and leakage radiation associated with a generic tomotherapy unit. A comparison is made with the shielding requirements for a conventional linear accelerator operated in a standard manner. Substantial differences in the amount of both primary and secondary shielding are indicated. A tomotherapy primary beam shield is both reduced in width by a factor of almost 10 and increased in thickness by more than a tenth value layer in comparison to a conventional accelerator. Furthermore, the secondary shielding requirements are enhanced by more than two tenth value layers with respect to conventional shielding demands.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.018
GPT teacher head0.312
Teacher spread0.294 · 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 designBench or experimental
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

Citations17
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueMedical PhysicsSame topicAdvanced Radiotherapy TechniquesFrench-language works237,207