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Record W4398784477 · doi:10.14740/ijcp532

Magnets Playing Hide and Seek: A Case Report of Hidden Magnets in a Child

2024· article· en· W4398784477 on OpenAlexvenueno aff
Yasir Ahmed, Pooneh Farhangi, Ibrar Atiq, Fahad Malik, Gregory Scagnelli

Bibliographic record

VenueInternational Journal of Clinical Pediatrics · 2024
Typearticle
Languageen
FieldMedicine
TopicRestraint-Related Deaths
Canadian institutionsnot available
Fundersnot available
KeywordsMagnetMedicineMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

With the now widespread use of small magnets in household items and toys, ingestion of these items has become a serious health hazard which carries the possibility of complications such as gastrointestinal (GI) tract perforation, hemorrhage, necrosis and death. While endoscopic retrieval of these objects has long been in practice, the possibility of the magnets attaching to the scope without practitioner's knowledge has not received sufficient attention in literature. Here we report a case of a 5-year-old female who was admitted for endoscopic retrieval of two small magnet ball bearings that she had swallowed shortly before admission. The search for the foreign objects was made difficult by ingested food obstructing the view. Fluoroscopy was also unremarkable. The procedure was ultimately deemed unsuccessful and terminated after 56 min. Both ball bearings were found attached to the scope upon inspection of the scope post procedure. Attachment of magnets to the scope should be a consideration during endoscopic removal, especially in cases of poor visibility. This can potentially help reduce unnecessary prolongation of procedures and therefore, complications including postoperative anesthesia symptoms, perforation, etc. Int J Clin Pediatr. 2024;13(1):34-37 doi: https://doi.org/10.14740/ijcp532

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.004
Open science0.0020.003
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.039
GPT teacher head0.415
Teacher spread0.376 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2024
Admission routes1
Has abstractyes

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