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Record W1995551246 · doi:10.14740/jmc.v6i2.2032

Diagnostic Confusion Caused by a Giant Appendicolith: A Case Report

2015· article· en· W1995551246 on OpenAlexvenueno aff
Kaushik Kumar, David M. Lewis

Bibliographic record

VenueJournal of Medical Cases · 2015
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineConfusionPresentation (obstetrics)AppendicitisAppendixAbdominal painRadiologyAcute appendicitisAbdomenLaparoscopyGeneral surgeryRadiological weaponAcute abdomenSurgery

Abstract

fetched live from OpenAlex

Acute appendicitis is one of the most common surgical emergencies worldwide. The diagnosis is usually a clinical one, supported by laboratory and radiological investigations as required. However, atypical clinical presentation and imaging can cause diagnostic confusion. Possibility of appendicolith in imaging in presence of abdominal pain and no urological pathology warrant diagnostic laparoscopy to rule out appendicitis, as appendicoliths are associated with complicated appendicitis particularly when they are large. We report a case of a 24-year-old male patient with clinical presentation suggestive of urological problem, and the imaging showed unusual large opacities in right lower abdomen with possibility of foreign body in small bowel or large fecalith. A diagnostic laparoscopy was performed where perforated appendix with large fecalith was confirmed. J Med Cases. 2015;6(2):71-73 doi: http://dx.doi.org/10.14740/jmc2032w

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)0.001
metaresearch head score (Gemma)0.006
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.003
Science and technology studies0.0050.003
Scholarly communication0.0030.005
Open science0.0020.004
Research integrity0.0070.005
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 head0.052
GPT teacher head0.343
Teacher spread0.291 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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