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Record W2056091143 · doi:10.1088/0031-9155/52/6/010

Dosimetric characterization of the irradiation cavity for accelerator-based <i>in vivo</i> neutron activation analysis

2007· article· en· W2056091143 on OpenAlexafffund
Soo Hyun Byun, Ana Pejović‐Milić, Scott A. McMaster, W Matysiak, Aslam, Z Liu, L.M. Watters, W. V. Prestwich, Fiona E. McNeill, David R. Chettle

Bibliographic record

VenuePhysics in Medicine and Biology · 2007
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsToronto Metropolitan UniversityMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIrradiationNeutronEquivalent doseNuclear medicineRadiochemistryNeutron temperatureMaterials scienceRadiationIn vivoPhysicsChemistryNuclear magnetic resonanceNuclear physicsMedicineBiology

Abstract

fetched live from OpenAlex

A neutron irradiation cavity for in vivo activation analysis has been characterized to estimate its dosimetric specifications. The cavity is defined to confine irradiation to the hand and modifies the neutron spectrum produced by a low energy accelerator neutron source to optimize activation per dose. Neutron and gamma-ray dose rates were measured with the microdosimetric technique using a tissue-equivalent proportional counter at the hand irradiation site and inside the hand access hole. For the outside of the cavity, a spherical neutron dose equivalent meter and a Farmer dosemeter were employed instead due to the low intensity of the radiation field. The maximum dose equivalent rate at the outside of the cavity was 2.94 microSv/100 microA min, which is lower by a factor of 1/2260 than the dose rate at the hand irradiation position. The local dose contributions from a hand, an arm and the rest of a body to the effective dose rate were estimated to be 1.73, 0.782 and 2.94 microSv/100 microA min, respectively. For the standard irradiation protocol of the in vivo hand activation, 300 microA min, an effective dose of 16.3 microSv would be delivered.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.118
GPT teacher head0.380
Teacher spread0.262 · 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

Citations33
Published2007
Admission routes2
Has abstractyes

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