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Record W1973527140 · doi:10.1093/rpd/ncp088

Canadian national internal dosimetry performance testing programme: results of the pilot programme

2009· article· en· W1973527140 on OpenAlexaffabout
Gary H. Kramer

Bibliographic record

VenueRadiation Protection Dosimetry · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRadiation Effects and Dosimetry
Canadian institutionsHealth Canada
Fundersnot available
KeywordsInternal dosimetryMedical physicsBioassayDosimetryCalibrationEnvironmental scienceEuropean commissionIn vivoTest (biology)MedicineNuclear medicineStatisticsBiotechnologyBiologyBusinessMathematicsEcology

Abstract

fetched live from OpenAlex

This paper describes the design and construction of a new performance testing programme that was implemented in Canada in 2008. The Canadian Regulator (Canadian Nuclear Safety Commission) had determined that their licensees, in addition to participating in the existing in vivo and in vitro performance tests, needed to demonstrate their ability in interpreting bioassay results to obtain intakes and resulting doses. The new programme is administered by the Canadian National Calibration Reference Center for Bioassay and In Vivo Monitoring (NCRC). Currently, the NCRC carries out the performance testing for the in vitro and in vivo. At the time of writing, the first round has been completed and the results for (3)H and (nat)U exposures were very consistent, while the committed effective dose from (137)Cs intake varied by a factor of two.

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)0.015
metaresearch head score (Gemma)0.007
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 score0.969
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.002
Scholarly communication0.0010.000
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.226
Teacher spread0.195 · 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

Citations0
Published2009
Admission routes2
Has abstractyes

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