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Record W2333101384 · doi:10.1097/hp.0000000000000444

Deposition Measurements From the Full-Scale Radiological Dispersal Device Field Trials

2016· article· en· W2333101384 on OpenAlexaffabout
Lorne Erhardt, Luke Lebel, Ed Korpach, Rodney Berg, Elizabeth Inrig, Ian Watson, Colleen Gilhuly, Debora Quayle

Bibliographic record

VenueHealth Physics · 2016
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsHuawei Technologies (Canada)Defence Research and Development CanadaCanadian Nuclear LaboratoriesHealth Canada
Fundersnot available
KeywordsDeposition (geology)PlumeRadiological weaponRadioactive contaminationEnvironmental scienceScale (ratio)Radiation monitoringRemote sensingRadionuclideMaterials scienceNuclear medicineRadiochemistryGeologyMeteorologyChemistryPhysicsNuclear physicsMedicineGeomorphology

Abstract

fetched live from OpenAlex

In 2012, Defence Research and Development Canada led a series of experiments, titled the Full-Scale Radiological Dispersal Device Field Trials, in which short-lived radioactive material was explosively dispersed and the resulting plume and deposition were characterized through a variety of methods. Presented here are the results of a number of measurements that were taken to characterize the radioactive ground deposition. These included in situ gamma measurements, deposition filter samples, and witness plate measurements that were taken in situ with handheld beta survey meters. The results from the different measurement techniques are compared to each other and to a simple deposition model. Results showed that approximately 3% of the original source activity was deposited in the immediate vicinity of ground zero, and an additional 15-30% of the original activity was deposited within 450 m of ground zero. Implications of these results for emergency response are discussed.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.110
GPT teacher head0.321
Teacher spread0.211 · 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 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

Citations23
Published2016
Admission routes2
Has abstractyes

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