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Record W3044022164 · doi:10.1002/ccr3.3153

A child with a foreign body in bronchus misdiagnosed as asthma

2020· article· en· W3044022164 on OpenAlexaff
Nagendra Chaudhary, Sandeep Shrestha, Om Kurmi

Bibliographic record

VenueClinical Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicForeign Body Medical Cases
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsMedicineForeign bodyBronchusForeign body aspirationForeign Body IngestionAsthmaRight Main BronchusLeft main bronchusBronchoscopyDifferential diagnosisRigid bronchoscopyIngestionSurgeryForeign BodiesPediatricsGeneral surgeryRespiratory diseaseLungInternal medicinePathology

Abstract

fetched live from OpenAlex

Foreign body ingestion should be considered as an important differential in a child with difficult asthma. We report an 11-year-old male child with foreign body aspiration who initially was diagnosed and treated as difficult asthma. Later on, he was diagnosed to have a foreign body in the right bronchus, which was successfully removed by flexible bronchoscopy.

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)0.007
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 score0.009
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0040.003
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0040.002

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 head0.042
GPT teacher head0.349
Teacher spread0.307 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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