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Record W1983821759 · doi:10.1118/1.2739816

On the physical, spectral, and dosimetric characteristics of a new brachytherapy source

2007· article· en· W1983821759 on OpenAlexaff
Rosana Pirchio, Eduardo Galiano, M. Saravi, David Banchik, Carlos Muñoz

Bibliographic record

VenueMedical Physics · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsLaurentian University
Fundersnot available
KeywordsBrachytherapyDosimetryMedical physicsMedical imagingRadiation therapyNuclear medicineMedicineRadiology

Abstract

fetched live from OpenAlex

A new 125I source under the name Braquibac has been developed in Argentina for interstitial brachytherapy applications. The aim of this work is to study the new seed's design and to calculate its dosimetric parameters. Radiographic and destructive tests were carried out on inactive seeds to determine the physical characteristics of the source. Values of g(r), Lambda, F(r, Theta), and phi(an)(r), were obtained in water and air by simulation using the MCNP5 Monte Carlo code according to the methodology recommended in TG-43 and updated in TG-43U1. The dose rate constant was determined to be 0.937+/-0.004 cGy h(-1) U(-1) (overall statistical uncertainty +/-2.7%). Sk per unity activity was calculated to be 0.671+/-0.003 cGy cm2 h(-1) mCi(-1) by simulation of the seed in dry air using point detectors. Spectroscopic studies for both the new and the Amersham model 6711 seed were performed using an HPGe planar detector. The emission spectra of both seeds proved to be very similar. The anisotropy of the total photon intensity in air was measured in planes containing the seed's short and long axes using the HPGe detector. The minimum photon intensity for the new seed was 31.14+/-3.10% of the transverse intensity.

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)0.000
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.282
Teacher spread0.272 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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