Acute hyponatraemia and 'ecstasy': insights from a quantitative and integrative analysis
Bibliographic record
Abstract
A 20-year-old woman attended a 'rave party' where she took the drug 3,4-methylenedioxymethamphetamine (MDMA, 'ecstasy'). She had used this drug previously without serious adverse effects. On this occasion, while both she and her friends drank a large quantity of water, only she became seriously ill. The initial manifestation was an altered sensorium; several hours later she had a grand mal seizure. In the Emergency Department, the most striking features were the severe degree of hyponatraemia (112 mmol/l) and cerebral oedema. To explain the basis for this life-threatening clinical presentation, an imaginary consultation was sought with Professor McCance. Using both a deductive and a quantitative analysis that involved several medical subspecialties, he illustrated that a simple story of water ingestion and vasopressin release was not sufficient to explain her hyponatraemia. It was only after events in her gastrointestinal tract were analysed that a plausible hypothesis could be constructed.
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 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".