MétaCan
Menu
Back to cohort
Record W3153093377 · doi:10.15669/pnst.1.529

An Analysis of Tritium Concentration in Urine Samples as a Function of Time after Intake

2011· article· en· W3153093377 on OpenAlexaboutno aff
Hee Geun Kim, Tae Young Kong, Woo Tae Jeong, Seok Tae Kim

Bibliographic record

VenueProgress in Nuclear Science and Technology · 2011
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicChemical Reactions and Isotopes
Canadian institutionsnot available
Fundersnot available
KeywordsTritiumUrineRenal functionRadiochemistryChemistryPhysicsNuclear physicsBiochemistry

Abstract

fetched live from OpenAlex

In pressurized heavy water reactors, workers who enter radiation controlled areas must submit urine samples to health physicists after radiation work; these samples are then used to monitor internal radiation exposure from tritium intake. But this procedure assumes that the samples submitted accurately represent tritium concentration inside the body at equilibrium. According to both technical reports from the International Commission on Radiological Protection and experimental results from Canadian nuclear utilities, tritium inside the body generally reaches equilibrium concentration after several hours of intake. In practice, urine samples can be submitted either before the 2-hour mark or after several hours of radiation work because of the numerous tasks workers must perform and their frequent entry during nuclear power plant maintenance. In this paper, tritium concentration in workers' urine samples was measured as a function of time submitted after radiation work. Based on the measurement results, changes in the tritium concentration inside the body and its effect on internal dose assessment were then analyzed. As a result, it was found that tritium concentration reaches equilibrium concentration before the 2-hour mark for most workers' urine samples.

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 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)0.000
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 score0.116
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.048
GPT teacher head0.377
Teacher spread0.329 · 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 teacher head, 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

Citations4
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueProgress in Nuclear Science and TechnologySame topicChemical Reactions and IsotopesFrench-language works237,207