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HML's WHOLE BODY COUNTER: MEASURING HIGHLY RADIOACTIVE PERSONS

2009· article· en· W2333374998 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Physics · 2009
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsHealth Canada
Fundersnot available
KeywordsNuclideWhole body countingImaging phantomMonte Carlo methodDetectorRadionuclideCalibrationCounting efficiencyRadiationBackground radiationEnvironmental sciencePhysicsNuclear engineeringNuclear physicsOpticsStatisticsMathematics

Abstract

fetched live from OpenAlex

The National Internal Radiation Assessment Section's Human Monitoring Laboratory (HML) has the responsibility to measure persons who may become internally contaminated following an accidental or intentional release of radioactivity. In preparation for measuring individuals who may be highly internally contaminated, the HML has reconfigured and recalibrated its whole body counter for this event. The calibration was performed using Monte Carlo simulations and validated by experimental measurements. An equation was developed that related the counting efficiency as a function of photon energy and phantom-to-detector distance. The equation could predict efficiencies to within 10% or better. Dead time problems, as a result of high internal activities, have been minimized by having a variety of counting positions. Six example nuclides have been used (Co, Co, Y, Ba, Cs, and Am) to show what is achievable and what is not.

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.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.119
GPT teacher head0.412
Teacher spread0.294 · 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