MétaCan
Menu
Back to cohort
Record W2756232648 · doi:10.2214/ajr.17.18087

Transatlantic Comparison of CT Radiation Doses in the Era of Radiation Dose–Tracking Software

2017· article· en· W2756232648 on OpenAlexaboutno aff
Anushri Parakh, André Euler, Zsolt Szucs‐Farkas, Sebastian T. Schindera

Bibliographic record

VenueAmerican Journal of Roentgenology · 2017
Typearticle
Languageen
FieldMedicine
TopicRadiation Dose and Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRadiation doseNuclear medicineRadiationTracking (education)Low Dose RadiationRadiation exposureMedical physicsRadiation oncologyRadiation therapyRadiologyDose–response relationshipOpticsInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study is to compare diagnostic reference levels from a local European CT dose registry, using radiation-tracking software from a large patient sample, with preexisting European and North American diagnostic reference levels. MATERIALS AND METHODS: ), dose-length product (DLP), size-specific dose estimate, and effective dose values for CT examinations of the head, paranasal sinuses, thorax, pulmonary angiogram, abdomen-pelvis, renal-colic, thorax-abdomen-pelvis, and thoracoabdominal angiogram were obtained using radiation-tracking software. Metrics from this registry were compared with diagnostic reference levels from Canada and California (published in 2015), the American College of Radiology (ACR) dose index registry (2015), and national diagnostic reference levels from local CT dose registries in Switzerland (2010), the United Kingdom (2011), and Portugal (2015). RESULTS: values by 55% for head, 240% for thorax, 28% for abdomen-pelvis, 42% for thorax-abdomen-pelvis, 128% for pulmonary angiogram, 138% for renal-colic, and 58% for paranasal sinus studies. CONCLUSION: Our local registry had lower diagnostic reference level values than did existing European and North American diagnostic reference levels. Automated radiation-tracking software could be used to establish and update existing diagnostic reference levels because they are capable of analyzing large datasets meaningfully.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.274

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.339
Teacher spread0.315 · 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

Citations22
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of RoentgenologySame topicRadiation Dose and ImagingFrench-language works237,207