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Record W2109125952 · doi:10.1093/rpd/ncm437

Effect of an aerosol deposition pattern in the lung on the counting efficiency of a large area germanium detector array

2007· article· en· W2109125952 on OpenAlexaff
Gary H. Kramer, B. M. Hauck

Bibliographic record

VenueRadiation Protection Dosimetry · 2007
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsDetectorCounting efficiencyDeposition (geology)HomogeneousAerosolPhotonRadionuclideGermaniumPlanarPhysicsDistribution (mathematics)Computational physicsPhoton countingSemiconductor detectorMaterials scienceBiological systemEnvironmental scienceOpticsNuclear physicsOptoelectronicsMathematicsSiliconStatistical physicsComputer scienceMeteorology

Abstract

fetched live from OpenAlex

The Human Monitoring Laboratory has extended the use of sliced lungs containing planar sources to simulate heterogeneous radionuclide deposition patterns. This work examined two deposition patterns and their effect on the counting efficiency of low-energy photons. The results have shown that heterogenous distributions can be difficult to detect in some cases and can still lead to large uncertainties (up to a factor of 2.5) in the activity estimate, especially at low photon energies. At higher energies ( approximately 60 keV), the effect of the heterogeneous distribution is greatly reduced and errors in the activity estimate reduced to approximately 25%. The presence of a heterogenous distribution can be detected by comparing the ratio of the individual detector counts with the expected values obtained from measuring multiple lungs sets that contained a homogeneous distribution. The distributions tested in this paper were detectable (at 2sigma) as heterogeneous by two of the four detectors in the counting array.

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)0.009
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.353
Teacher spread0.327 · 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 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

Citations2
Published2007
Admission routes1
Has abstractyes

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