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Record W2097606682 · doi:10.1093/rpd/nct161

Use of digital dosemeters for supporting staff radiation safety in paediatric interventional radiology suites

2013· article· en· W2097606682 on OpenAlex
Sarah M. McNeil, Patrick F.H. Lai, Bairbre Connolly, Christopher L. Gordon

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRadiation Protection Dosimetry · 2013
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsHospital for Sick ChildrenMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsMedical physicsMedicineRadiation protectionNuclear medicineRadiation doseInterventional radiologyElectromagnetic shieldingRadiation oncologyRadiologyRadiation therapyPhysics

Abstract

fetched live from OpenAlex

Modern-day interventional radiology (IR) procedures impart a wide range of occupational radiation doses to team members. Unlike thermoluminescent badges, digital dosemeters provide real-time dose readings, making them ideal for identifying different components during IR procedures, which influence staff radiation safety. This study focused solely on paediatric IR (PIR) cases. Digital dosemeters measured the impact of imaging modality, shielding, patient and operator specific factors, on the radiation dose received during various simulated and real live PIR procedures. They recorded potential dose reductions of 10- to 100-fold to each staff member with appropriate use of shielding, choice of imaging method, staff position in the room and complex interplay of other factors. The digital dosemeters were well tolerated by staff. Results highlight some unique radiation safety challenges in PIR that arise from dose increases with magnification use and close proximity of staff to the X-ray beam.

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.

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)0.002
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 score0.721
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.025
GPT teacher head0.284
Teacher spread0.259 · 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