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Record W2618302384 · doi:10.1097/bcr.0000000000000595

Patient With Scald Burn of the Esophagus

2017· article· en· W2618302384 on OpenAlexaff
Robert Kraft, Kai‐Ole Jensen, Marc G. Jeschke, Christian W. Schinkel

Bibliographic record

VenueJournal of Burn Care & Research · 2017
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineEsophagusSwallowingChemical burnComputed tomographyRadiologySurgeryProton-pump inhibitorIntravenous contrastGastroenterology

Abstract

fetched live from OpenAlex

Burns of the esophagus are usually caused by chemical substances. In our report, we present a case of burn injury burn caused by swallowing boiling water under the influence of controlled substances. During the initial diagnostic procedures, a CT scan was performed. In contrast, in the later on performed gastroscopy, the computed tomography (CT scan) revealed intramural and free air. A conservative treatment was started including parenteral nutrition, application of a nasogastric tube, and administration of proton pump inhibitor (PPIs). We conclude that for diagnosing the extend of a burn of the esophagus, a CT scan should be performed in addition to endoscopic procedures.

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)0.002
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.049
GPT teacher head0.386
Teacher spread0.338 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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