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Record W3123229880 · doi:10.1088/1361-6498/abdd06

The National Dose Registry—Canadian occupational exposure to ionising radiation, 1998–2018

2021· article· en· W3123229880 on OpenAlexaffabout
Jing Chen, Tim Prendergast, Philippe Prince, Adelene Gaw, Debora Quayle

Bibliographic record

VenueJournal of Radiological Protection · 2021
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsMedicineEnvironmental healthCollective doseRadiation exposureIonizing radiationEffective dose (radiation)Identification (biology)ToxicologyNuclear medicineBiology

Abstract

fetched live from OpenAlex

The National Dose Registry (NDR) is owned and operated independently by Health Canada. This paper provides an overview of how the registry operates within the Canadian regulatory structure, followed by an analysis of annual effective dose trends in nine job classes with relatively higher mean annual effective doses, i.e. greater than 1 mSv as reported in 2017. The analysis showed that, with a few exceptions, mean annual effective doses have generally decreased or remained practically unchanged in the past two decades at relatively low exposure levels. This review of occupational dose trends is evidence of the effectiveness of radiation protection programmes in Canada. The NDR has played an important role in the identification of relatively higher dose records and allowed the regulatory bodies to act immediately to ensure appropriate actions were taken.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.510
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.000
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 head0.043
GPT teacher head0.308
Teacher spread0.265 · 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 designNot applicable
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

Citations9
Published2021
Admission routes2
Has abstractyes

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