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Record W2325845526 · doi:10.1093/rpd/ncs014

Lung counting: comparison of detector performance with a four detector array that has either metal or carbon fibre end caps, and the effect on mda calculation

2012· article· en· W2325845526 on OpenAlexaff
A. S. Ahmed, B. M. Hauck, Gary H. Kramer

Bibliographic record

VenueRadiation Protection Dosimetry · 2012
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsDetectorImaging phantomMonte Carlo methodMaterials scienceTorsoSemiconductor detectorCounting efficiencyOpticsNuclear medicinePhysicsBiomedical engineeringMedicineMathematics

Abstract

fetched live from OpenAlex

This study described the performance of an array of high-purity Germanium detectors, designed with two different end cap materials-steel and carbon fibre. The advantages and disadvantages of using this detector type in the estimation of the minimum detectable activity (MDA) for different energy peaks of isotope (152)Eu were illustrated. A Monte Carlo model was developed to study the detection efficiency for the detector array. A voxelised Lawrence Livermore torso phantom, equipped with lung, chest plates and overlay plates, was used to mimic a typical lung counting protocol with the array of detectors. The lung of the phantom simulated the volumetric source organ. A significantly low MDA was estimated for energy peaks at 40 keV and at a chest wall thickness of 6.64 cm.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.755

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.335
Teacher spread0.266 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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