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The HML???s New Field Deployable, High-Resolution Whole Body Counter

2005· article· en· W2019448107 on OpenAlexaff
Gary H. Kramer, Kevin Capello, Barry M. Hauck

Bibliographic record

VenueHealth Physics · 2005
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsActivation LaboratoriesHealth Canada
Fundersnot available
KeywordsLaptopCalibrationCounting efficiencyGloveboxMonte Carlo methodNuclear engineeringSensitivity (control systems)Nuclear physicsPhysicsComputer scienceSimulationOpticsDetectorEngineeringMathematicsOperating systemStatisticsElectronic engineering

Abstract

fetched live from OpenAlex

The Human Monitoring Laboratory has found an alternate use for a hyperpure germanium field deployable instrument that was originally designed to be used in a search and identify mode for contraband radioactive material. The instrument, the Ortec Detective, becomes a fully functional spectroscopy system when connected to a laptop computer. In this configuration it can be used as a high-resolution portable whole body counter. This work has determined that the instrument has adequate sensitivity for emergency response with respect to fission and activation products, but not actinides. The use of Monte Carlo simulations has allowed the HML to calibrate the instrument, partially optimize the counting geometry, and develop a calibration curve that is a function of photon energy and a person's size. Similarly for thyroid counting, a function has been found that fits counting efficiency to a person's height. The MDA's are a few kilo Becquerels for fission and activation products for a 5-min count in an unshielded environment using a male subject.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.003

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 head0.070
GPT teacher head0.405
Teacher spread0.336 · 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

Citations17
Published2005
Admission routes1
Has abstractyes

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