Bibliographic record
Abstract
This article opens with a survey of the works of those physicians who, in the eighteenth century, expanded on the Classical and Renaissance theorization of hypochondria. It then looks at the connections between hypochondria and literary creation, a theme which is explored by several Italian eighteenth-century authors, among them Bernardino Ramazzini, Antonio Fracassini, Antonio Pujati, and Giovanni Verardo Zeviani. The study of the literati's hypochondria was very much in fashion in eighteenth-century Italy, as — on the other hand — at the peak of the grand tour craze it was fashionable, in the land of Dante, to declare oneself affected by the "English malady." The essay then focuses on the links between medicine and poetry with an examination of the literary creations of Italian and English poet-physicians who provided an exposition in verse of this 'disease of the learned.' Ultimately, science seems to confirm that the effort to defy mortality through knowledge and artistic achievement is a vain but unavoidable attempt, and that man in the age of reason suffers, more that ever before, from the unruly disease of an altered imagination.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".