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Record W2035171949 · doi:10.1088/0952-4746/30/2/002

An estimation of the annual effective dose to the Canadian population from medical CT examinations

2010· article· en· W2035171949 on OpenAlexaffabout
Jing Chen, D. Moir

Bibliographic record

VenueJournal of Radiological Protection · 2010
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsMedicineEffective dose (radiation)Per capitaNuclear medicineCollective dosePopulationRadiation doseMedical radiationMedical physicsComputed tomographyMedical imagingRadiation protectionRadiologyEnvironmental health

Abstract

fetched live from OpenAlex

This study was carried out to assess the annual per capita effective dose from medical diagnostic procedures using computed tomography (CT) in Canada. Relevant data concerning the nature and the frequency of various diagnostic CT examinations were obtained from the reports on Medical Imaging in Canada and Diagnostic Services in Ontario. Doses associated with examinations of different types were based primarily on typical effective doses used in the National Council on Radiation Protection and Measurements Report 160 with considerations of limited dose information surveyed in Canada. The results show that the per capita annual effective dose from diagnostic CT exams was 0.74 mSv in 2006, up from 0.19 mSv in 1991. This significant increase in population radiation dose from CT scans is due mainly to a more than doubling in the examination rate and to a higher radiation dose per procedure from the newer generation of multi-detector CTs.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.928
Threshold uncertainty score0.989

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 integrity0.0000.001
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 head0.011
GPT teacher head0.290
Teacher spread0.279 · 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

Citations15
Published2010
Admission routes2
Has abstractyes

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