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Record W3035462435 · doi:10.14288/1.0085759

The absolute dosimetry of negative pions

2010· article· en· W3035462435 on OpenAlexaboutno aff
Kenneth Robert Shortt

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
Fundersnot available
KeywordsDosimetryAbsolute (philosophy)PionPhysicsNuclear physicsNuclear medicineMedicinePhilosophy

Abstract

fetched live from OpenAlex

Soon three centres will be treating cancer with beams of negative pions: LAMPF, Los Alamos, U.S.A.; SIN, Villigen, Switzerland; and TRIUMF, Vancouver, Canada. In order to understand this new modality, it will be necessary to compare the results of pion therapy to those achieved with conventional means and to compare results among the three centres. Absolute dosimetry is the basis of this comparison. An absolute dose determination has been made for the negative pion beam at TRIUMF. using an ionization chamber. The relationship required to convert the ionization per unit mass, J/M, measured by the chamber to dose in tissue is D = J/M W r F where W, r and F are calculated quantities. W is the average energy expended in the gas per ion pair produced. Since the W-value for a secondary liberated during pion capture depends upon its energy, it was necessary to average over the energy spectra for the various secondaries. r is the ratio of dose in the wall material, carbon, to dose in the gas, either methane or carbon dioxide. Since the pion secondaries have ranges which are of the same size as the cavity of the ion chamber, it was necessary to explicitly consider those secondaries which emerge from the wall with insufficient energy to cross the cavity and those pions which form stars inside the cavity. Thus, r was found to be pressure dependent. The pressure dependence for carbon dioxide arises as follows:- as the pressure is increased, there are more pion captures in the gas, but since there is less energy released to charged secondaries per pion capture on oxygen than carbon, the dose in the gas decreases. Therefore, the calculation predicted that, as pressure is increased, J/M would remain unchanged for methane, but would decrease rather dramatically for carbon dioxide. F is the ratio of dose in tissue to dose in wall material, carbon in this case. F is the product of two factors: P, which accounts for the difference in the stopping pion density for tissue compared to carbon, and K, which accounts for the difference in energy released per pion capture in tissue compared to carbon. Experimentally, the ionization per unit mass was measured in a parallel plate chamber as a function of pressure for various gases with carbon, aluminum and TE-A150 electrodes. The pressure dependence of J/M measured for methane and carbon dioxide with carbon electrodes was compared to the behavior predicted by the calculation. Qualitatively, the prediction was confirmed: the ionization per unit mass for CO₂ decreases more dramatically with increased pressure than for CH₄. Therefore pion capture in the gas is significant and the energy released to charged secondaries per pion capture on oxygen is less than for carbon. Quantitatively, the percentage change is larger than predicted. The value of J/M extrapolated to zero pressure and the appropriate values calculated for W and r enabled a determination of the absolute dose in carbon with an estimated accuracy of ± 5%. The ionization created with aluminum electrodes was compared to that for carbon in order to estimate the dose in aluminum. After considering the dose contribution from beam contaminants, the value of F required to convert dose in carbon to dose in tissue was estimated to be 0.93 ± 0.05. Therefore, the absolute dose in tissue was determined to an accuracy of ± 7%. In order to increase the accuracy, it is necessary to improve the data available as input to the calculation.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.003
GPT teacher head0.140
Teacher spread0.137 · 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 designObservational
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

Citations0
Published2010
Admission routes1
Has abstractyes

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