Cocaine ‘body packers’ and the clinical management of packet rupture
Bibliographic record
Abstract
A 43-year-old Afro-Caribbean man was behaving oddly in the arrivals lounge at London Heathrow Airport. He was agitated, sweating profusely and disorientated. Urinalysis was positive for cocaine, and he was transferred to the local accident and emergency department. On arrival, he was hyperactive, tachycardic (rate 140/min), hypertensive (blood pressure 235/140 mmHg) and agitated. A plain abdominal radiograph identified multiple, well-defined objects throughout the gastrointestinal tract (Figure 1) with no evidence of bowel obstruction. Whole bowel irrigation with polyethylene glycol (2 litres/hour orally) was started. The patient remained agitated and hypertensive despite aggressive medical treatment for cocaine toxicity using intravenous diazepam (total 45 mg intravenously over 2 hours) and glyceryl trinitrate (maximum infusion rate 8 mg/hr). Following surgical consultation, it was decided to perform a laparotomy (Figures 2a and b). In total, 89 packets of cocaine were surgically removed from the stomach, small and large bowel (Figure 2c), with an estimated street value of £50 000–100 000 depending on purity. Postoperatively the patient made an uneventful recovery.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| 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".