Bibliographic record
Abstract
ABSTRACT: We report a rare case of a young child, younger than10 years, who died of complications related to trichophagia and multiple gastrointestinal trichobezoars. One year before death, the child's clinical history yielded a diagnosis of iron deficiency anemia, believed to be related to poor diet, and alopecia areata, the etiology of which was unknown. Two weeks before death, the child presented with complaints of intermittent "flu-like" symptoms and vomiting. The child reported abdominal pain, anorexia, and fatigue on the night before death. The next morning, the child ate breakfast and was subsequently discovered unresponsive.On external examination, there were areas of thinning head hair. Postmortem computed tomography, magnetic resonance imaging, and internal examination revealed 3 distinct trichobezoars, occupying the stomach, jejunum, and ileum. This was complicated by small bowel obstructions and perforations due to the trichobezoars. The cause of death was peritonitis secondary to small bowel perforations due to small bowel obstruction with multiple trichobezoars. This is the first case report to demonstrate the utility of postmortem computed tomography and magnetic resonance imaging in characterizing the nature and extent of trichobezoars in a fatal case of Rapunzel syndrome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".