Bibliographic record
Abstract
Hyoscyamus, the henbane, is one of the drugs of the ancients. Initially used both as a poison and narcotic, it was widely adopted by witches, wizards and soothsayers as a component of their hallucinatory and flying ointments. It was also used by notorious poisoners such as Madame Voisin in France. Eventually, in the nineteenth century its active principle was isolated by Ladenburg and called l-hyoscine. It proved to be a tropane alkaloid very similar to atropine. These two alkaloids proved to be very important in the study of the parasympathetic component of the autonomic nervous system, and together with physostigmine, allowed the major neurotransmitter acetylcholine to be isolated and its mechanisms of action to be characterised. The Crippen murder case in 1910 gave hyoscine further fame, indeed, notoriety. The unassuming homeopathic doctor murdered his wife with the alkaloid and then decamped for Canada with his mistress Ethel Le Neve. The case became a worldwide sensation for several reasons: the arrest of the fugitive couple by wireless telegraphy (Marconigram) and the extensive chemical and histological evidence presented by Willcox and Spilsbury. Some authorities claim that this was the beginning of the science of forensic medicine in Britain. Hyoscine is now hardly ever used in modern therapeutics but its history from antiquity to the witches and on to Dr Crippen is both bizarre and fascinating.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.010 |
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".