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Record W2331057569 · doi:10.1177/0146645316637786

Internet-based ICRP resource for healthcare providers on the risks and benefits of medical imaging that uses ionising radiation

2016· article· en· W2331057569 on OpenAlexaff
S. Demeter, Kimberly E. Applegate, María del Rosario Pérez

Bibliographic record

VenueAnnals of the ICRP · 2016
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsUniversity of ManitobaHealth Sciences Centre
FundersWorld Health Organization
KeywordsIonizing radiationHealth careBusinessMedical physicsResource (disambiguation)Risk analysis (engineering)The InternetMedicineEnvironmental healthComputer sciencePolitical scienceWorld Wide WebPhysics

Abstract

fetched live from OpenAlex

The purpose of the International Commission on Radiological Protection (ICRP) Committee 3 Working Party was to update the 2001 web-based module 'Radiation and your patient: a guide for medical practitioners' from ICRP. The key elements of this task were: to clearly identify the target audience (such as healthcare providers with an emphasis on primary care); to review other reputable sources of information; and to succinctly publish the contribution made by ICRP to the various topics. A 'question-and-answer' format addressing practical topics was adopted. These topics included benefits and risks of imaging using ionising radiation in common medical situations, as well as pertaining to specific populations such as pregnant, breast-feeding, and paediatric patients. In general, the benefits of medical imaging and related procedures far outweigh the potential risks associated with ionising radiation exposure. However, it is still important to ensure that the examinations are clinically justified, that the procedure is optimised to deliver the lowest dose commensurate with the medical purpose, and that consideration is given to diagnostic reference levels for particular classes of examinations.

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 score0.802
Threshold uncertainty score0.174

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 head0.166
GPT teacher head0.374
Teacher spread0.208 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the ICRPSame topicRadiation Dose and ImagingFrench-language works237,207