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RADIOLOGICAL HAZARD ESTIMATES FROM CONTAMINATED C7 CANISTERS ON THE C4 PROTECTIVE MASK

2009· article· en· W2000021566 on OpenAlexaffabout
Edward Waller, Lorne Erhardt

Bibliographic record

VenueHealth Physics · 2009
Typearticle
Languageen
FieldEngineering
TopicNuclear and radioactivity studies
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsRadiological weaponEnvironmental scienceHazardContaminationRadiation protectionRadioactive wasteRadioactive contaminationNuclear engineeringEquivalent doseWaste managementComputer scienceForensic engineeringNuclear medicineRadiochemistryEngineeringDosimetryChemistryMedicine

Abstract

fetched live from OpenAlex

This study compares the external hazard posed by radioactive material trapped in the C7 filter canister of the Canadian C4 full-face mask to the internal hazard from the portion of the material that bypasses the mask and is inhaled. Published measured protection factors (PFs) are used to define the ratio of radioisotope concentration outside of the mask to that inside the mask. The hazards for a variety of radioisotopes are quantified using a Monte Carlo model for the external hazard from the contaminated canister and International Commission on Radiological Protection Publication 68 internal dose coefficients for 1 micron internalized particulate material. In general, the external hazard from a contaminated canister exceeds the internal hazard from material that bypasses the filters for only the most highly protective negative-pressure masks and then only for gamma emitting materials. Our model shows that it is highly unlikely that a canister can become contaminated with enough radioactive material to pose an immediate threat to the wearer, even for pessimistic radiological dispersal device scenarios, when the mask is being worn properly. The "as low as reasonably achievable" (ALARA) principle, however, suggests that filters should be changed as frequently as practical, and the dose measured in the filter may be useful for determining dose of record and for forensic investigations.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.257
Teacher spread0.229 · 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 designSimulation or modeling
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
Published2009
Admission routes2
Has abstractyes

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