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Record W1943050010 · doi:10.3109/01443615.2015.1017559

A case series of 15 women inadvertently exposed to magnetic resonance imaging in the first trimester of pregnancy

2015· article· en· W1943050010 on OpenAlexaff
Ji Soo Choi, Heungju Ahn, Jin‐Yeong Han, You Jung Han, D. O. Kwak, E. Yadira Velázquez-Armenta, Alejandro A. Nava‐Ocampo

Bibliographic record

VenueJournal of Obstetrics and Gynaecology · 2015
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineMagnetic resonance imagingPregnancyFirst trimesterRadiologyObstetricsUltrasoundPelvisGestation

Abstract

fetched live from OpenAlex

Information on the safety of first-trimester exposure to diagnostic magnetic resonance imaging (MRI) remains scarce. We are reporting a case series of 15 consecutive pregnant women who underwent an MRI scan with a 1.5-Tesla scanner of either the head (n = 5), cervical spine (n = 4), lumbar spine (n = 4), pelvis (n = 1) or knee (n = 1) in their first trimester of pregnancy (mean gestational age at exposure: 3.8 weeks). Patients were prospectively followed up until the completion of their pregnancy. Two cases received gadolinium as a contrast agent. There were 15 babies born alive. Of them, one baby was born with the left kidney not visualised by ultrasound examination, and another one with an overlapping toe in the right foot. None of these abnormalities were considered by the authors related to the MRI exposure. In conclusion, our study provides support to published preliminary evidence regarding the safety of MRI in the first-trimester pregnant women.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.215
Teacher spread0.198 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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