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Record W4403309767 · doi:10.14740/jmc4280

Ingested Magnets Found Inadvertently During Elective Magnetic Resonance Imaging

2024· article· en· W4403309767 on OpenAlexvenueno aff
Jennifer Sawyer, Lance M. Relland, Molly S. Hagele, Joseph D. Tobias

Bibliographic record

VenueJournal of Medical Cases · 2024
Typearticle
Languageen
FieldMedicine
TopicForeign Body Medical Cases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMagnetic resonance imagingMagnetNuclear magnetic resonanceRadiologyMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

In the presence of a strong magnetic field such as for magnetic resonance imaging (MRI), ferromagnetic objects may become a source of patient or healthcare provider injury. To prevent such problems, careful screening of patients and healthcare workers is mandatory prior to MRI to identify contraindications to MRI including the presence of external or internal ferromagnetic products. We present a 2-year, 11-month-old child who presented for MRI to evaluate a potential vertebral anomaly. During initial scanning and image acquisition, image distortion was noted which was subsequently determined to be the result of ingested magnetic objects. The basic principles of MRI are discussed, safety pathways to prevent patient and practitioner risk related to ferromagnetic objects presented, and previous reports of patient-related adverse effects from internal ferromagnetic devices reviewed.

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)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.302
Teacher spread0.285 · 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.

Study designCase report
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

Citations1
Published2024
Admission routes1
Has abstractyes

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