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Record W2009819542 · doi:10.1097/hp.0b013e318213b9e6

RAPID DETERMINATION OF URANIUM ISOTOPES IN URINE BY INDUCTIVELY COUPLED PLASMA-MASS SPECTROMETRY

2011· article· en· W2009819542 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 · 2011
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsAtomic Energy (Canada)
FundersArgonne National Laboratory
KeywordsUraniumInductively coupled plasma mass spectrometryDepleted uraniumIsotopes of uraniumChemistryMass spectrometryUrineRadiochemistryChromatographyIsotopeSample preparationInductively coupled plasmaMaterials sciencePlasmaNuclear physics

Abstract

fetched live from OpenAlex

Following a radiological or nuclear emergency involving uranium exposure, rapid analytical methods are needed to analyze the concentration of uranium isotopes in human urine samples for early dose assessment. The inductively coupled plasma mass spectrometry (ICP-MS) technique, with its high sample throughput and high sensitivity, has advantages over alpha spectrometry for uranium urinalysis after minimum sample preparation. In this work, a rapid sample preparation method using an anion exchange chromatographic column was developed to separate uranium from the urine matrix. A high-resolution sector field ICP-MS instrument, coupled with a high sensitivity desolvation sample introduction inlet, was used to determine uranium isotopes in the samples. The method can analyze up to 24 urine samples in two hours with the limits of detection of 0.0014, 0.10, and 2.0 pg mL(-1) for (234)U, (235)U, and (238)U, respectively, which meet the requirement for isotopic analysis of uranium in a radiation emergency.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

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

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 head0.126
GPT teacher head0.374
Teacher spread0.248 · 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