Faria’s disease, a fictional character in search of a diagnosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Some years ago I wrote about the medical material in Alexandre Dumas’s The Count of Monte Cristo and indicated that it was not only rich and varied but remarkably accurate for a non-physician writer.1, 2 For example, he described the locked-in syndrome in the character Monsieur Noirtier de Villefort 120 years before the seminal article by Plum and Posner in 1966. A list of some of the conditions, medications and procedures in the The Count of Monte Cristo is shown in the table. View this table: Table Medical matters in The Count of Monte Cristo As a young aspiring writer, Dumas learned about medicine from a young medical graduate of the University of Paris, Dr A Thibauld, who taught him anatomy, physiology, toxicology and other medical facts in his rooms each evening. Dr Thibauld also took Dumas on hospital medical rounds to see patients suffering from various ailments. Dumas had a writer’s interest in observing cases as potential material, learning the details of conditions he could later use in his novels. As he said in his autobiography, he used the lessons from Dr Thibauld in his writings for the next 30 years.3 Alexandre Dumas was a remarkable man who led a remarkable life and left a body of lasting literature that is probably greater than any other writer. He wrote over 600 books (no one is sure how many), and no one has read all of Dumas. He wrote constantly and often four or five books at a time, publishing a shelf of books …
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it