Bibliographic record
Abstract
Unrelenting illness plagued Beethoven throughout his entire adult life. His disorder (or disorders) produced myriad physical and psychological torments, the etiology of which has never been diagnosed definitively. For him the most distressing consequence of his illness was its effect on the auditory nerves, which it left shrunken and useless after causing years of pain and ringing in the ears. The disorder's most lethal effect, however, was its destruction of the liver, which it rendered fibrotic and riddled with nodules “the size of a bean” (135), causing secondary ascites, an enlarged spleen, nose bleeds, and bleeding esophageal varices. These were its dominant features. However, numerous other associated abnormalities have complicated efforts to identify a unifying diagnosis. There were decades of recurrent abdominal pain and diarrhea, attacks of bronchitis and feverish catarrhs (with no gross postmortem pulmonary pathology), repeated episodes of rheumatism, tormenting headaches, and postmortem abnormalities of the brain, pancreas, and kidneys. There were also possible episodes of smallpox and typhus, heavy alcohol consumption, a family history of alcoholism, sexual promiscuity (at least late in life), and high levels of lead detected in samples of hair analyzed over a century and a half after the composer's death.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".