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Record W3154908129 · doi:10.1088/1361-6498/abf901

The optimisation of paediatric CT examinations in Scotland: phase one; benchmarking current performance

2021· article· en· W3154908129 on OpenAlexfundno aff
Mark Worrall, Nicola MacDonald, Rebecca Gillen, Andrew Hince, Lee Hampson, Rebecca Duguid, Stephen McCallum, David Gentle

Bibliographic record

VenueJournal of Radiological Protection · 2021
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsnot available
FundersHospital for Sick Children
KeywordsImaging phantomMedicineScannerComputed tomographyNuclear medicineMedical physicsProtocol (science)RadiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract To benchmark the dose from paediatric head and chest examinations on computed tomography (CT) scanners throughout Scotland, to identify scanners that may require optimisation and to provide optimisation advice based on the protocols from better performing scanners. Anthropomorphic phantoms corresponding to 1, 5 and 10 year olds were sent to 50 CT scanners around Scotland. Head and chest examinations were undertaken by local staff using local techniques on each scanner with each phantom, and details of the protocols used were recorded. Computed tomography dose index (CTDI) vol and dose length product (DLP) were recorded post-scan. There is a significant variation in performance throughout Scotland. For head examinations, the highest DLP is 13 times the lowest for an equivalent sized phantom. For chest examinations, the highest is 128 times the lowest for an equivalent sized phantom. The wide range of CT dose measurements indicates the potential for variation in image quality across Scotland. Feedback has been provided to all participating sites on their individual results compared to the national data set. Specific feedback was provided where relevant on potential considerations for optimisation. Scanners that may be undertaking paediatric CT head and chest examinations in a sub-optimal manner throughout Scotland have been identified along with those aspects of a scan protocol that are most likely to lead to sub-optimal performance.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.161

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.051
GPT teacher head0.316
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 designOther design
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

Citations3
Published2021
Admission routes1
Has abstractyes

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