Bibliographic record
Abstract
Guillaume-Benjamin-Amand Duchenne was born 200 years ago in Boulogne-sur-Mer (Pas-de-Calais, France). He studied medicine in Paris and became a physician in 1831. He practiced general medicine in his native town for about 11 years and then returned to Paris to initiate pioneering studies on electrical stimulation of muscles. Duchenne used electricity not only as a therapeutic agent, as it was commonly the case earlier in the 19th century, but chiefly as a physiological investigation tool to study the anatomy of the living body. Without formal appointment he visited hospital wards across Paris searching for rare cases of neuromuscular disorders. He built a portable electrical device that he used to functionally map all bodily muscles and to study their coordinating action in health and disease. He gave accurate descriptions of many neuromuscular disorders, including pseudohypertrophic muscular dystrophy to which his name is still attached (Duchenne muscular dystrophy). He also invented a needle system (Duchenne's histological harpoon) for percutaneous sampling of muscular tissue without anesthesia, a forerunner of today's biopsy. Duchenne summarized his work in two major treatises entitled De l'électrisation localisée (1855) and Physiologie des mouvements (1867). Duchenne's iconographic work stands at the crossroads of three major discoveries of the 19th century: electricity, physiology and photography. This is best exemplified by his investigation of the mechanisms of human physiognomy in which he used localized faradic stimulation to reproduce various forms of human facial expression. The album that complements his book on this issue is considered a true incunabulum of photography. Duchenne de Boulogne, a shy but hard-working, acute and ingenious observer, became one of most original clinicians of the 19th century. He died in Paris in 1875.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.007 |
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".