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Record W2108722027 · doi:10.1093/rpd/ncq161

Selectivity of 90Sr urine bioassay technique over 241Am, 238/239PU, 210PO, 137CS and 60CO

2010· article· en· W2108722027 on OpenAlexaff
Baki Sadi, Chunsheng Li, Negar Bahraini, Edward P. C. Lai, Gary H. Kramer

Bibliographic record

VenueRadiation Protection Dosimetry · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsCarleton UniversityHealth Canada
FundersNational Institute of Standards and Technology
KeywordsLibrary scienceMedicineComputer science

Abstract

fetched live from OpenAlex

The selectivity of a rapid 90Sr bioassay technique over 241Am, 238/239Pu, 210Po, 137Cs and 60Co has been investigated. Similar to 90Sr, these radionuclides are likely to be used in radiological dispersive devices. The purpose of this study was to demonstrate the degree to which the 90Sr bioassay technique is free from interference by these radionuclides if present in a urine matrix. The interfering radionuclides were removed (from 90Sr) by their retention on an anion exchange column. While, recovery of the target radionuclide (90Sr) was found to be ≥ 90 %, contributions from 241Am, 242Pu and 208Po were found to be ≤ 3 % indicating minimal interference from these radionuclides. The breakthrough for 60Co, however, was found to be ≤19 % indicating that it will have some interference contribution to the 90Sr measurement if present in the urine sample. As 137Cs was not retained at all by the anion exchange column, the method as such was not selective over 137Cs. However, a slight modification of the method through the ammonium molybdophosphate treatment quantitatively removed Cs from the urine sample, thereby; making it selective for 90Sr despite any 137Cs that is present.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.004
GPT teacher head0.211
Teacher spread0.207 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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