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Record W35026745 · doi:10.1088/1361-6560/ac4b36

Construir y decorar

2008· article· en· W35026745 on OpenAlexfundno aff
Rodrigo de la Torre Martín-Romo

Bibliographic record

VenueRománico: Revista de arte de amigos del románico ( AdR ) · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture, Art, Education
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer science

Abstract

fetched live from OpenAlex

With the integration of treatments with MRI-linacs to the clinical workflow, the understanding and characterization of detector response in reference dosimetry in magnetic fields are required. The external magnetic field perturbs the electron fluence. The degree of perturbation depends on the irradiation conditions and on the detector type. The purpose of this study is to evaluate the magnetic field impact on the electron fluence spectra in several detectors to provide a deeper understanding of detector response in these conditions. Monte Carlo calculations of the electron fluence are performed in six detectors (solid-state: PTW60012 and PTW60019, ionization chambers: PTW30013, PTW31010, PTW31021, and PTW31022) in water and irradiated by a 7 MV FFF photon beam with a small and a reference field, at 0 and 1.5 T. Three chamber axis orientations are investigated: parallel or perpendicular (either the Lorentz force pointing towards the stem or the tip) to the magnetic field and always perpendicular to the photon beam. One orientation for the solid-state detector is studied: parallel to the photon beam and perpendicular to the magnetic field. Additionally, electron fluence spectra are calculated in modified detector geometries to identify the underlying physical mechanisms behind the fluence perturbations. The total electron fluence in the Farmer chamber varies up to 1.24% and 5.12% at 1.5 T, in the parallel and perpendicular orientation, respectively. The interplay between the gyration radius and the Farmer chamber cavity length significantly affects the electron fluence in the perpendicular orientation. For the small-cavity chambers, the maximal variation in total electron fluence is 0.19% in the parallel orientation for the reference field. Significant small-field effects occur in these chambers; the magnetic field reduces the total electron fluence (with respect to the no field case) between 9.86% and 14.50%, depending on the orientation. The magnetic field strongly impacted the solid-state detectors in both field sizes, probably due to the high-Z components and cavity density. The maximal reductions of total electron fluence are 15.06 ± 0.09% (silicon) and 16.00 ± 0.07% (microDiamond). This work provides insights into detector response in magnetic fields by illustrating the interplay between several factors causing dosimetric perturbation effects: (1) chamber and magnetic field orientation, (2) cavity size and shape, (3) extracameral components, (4) air gaps and their asymmetry, (5) electron energy. Low-energy electron trajectories are more susceptible to change in magnetic fields, and are associated with detector response perturbation. Detectors with higher density and high-Z extracameral components exhibit more significant perturbations in the presence of a magnetic field, regardless of field size.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.027
GPT teacher head0.236
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2008
Admission routes1
Has abstractyes

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