Dr. Henry Head and lessons learned from his self-experiment on radial nerve transection
Bibliographic record
Abstract
In this paper the authors aim to review Dr. Henry Head's famous and dramatic nerve sectioning experiment. They discuss the implications of his experimental approach as well as the effect his experiment had on the field of neurology. Henry Head was a prominent British neurologist who contributed greatly to the understanding of the sensory examination through an experiment in which he had his own radial nerve transected. Head carefully documented the sensory changes following the sectioning. He hypothesized the existence of two separate sensory systems: protopathic and epicritic. Head was one of the first scientists to speculate on sensory dissociation, and his writings generated both enthusiasm and controversy. Although the ethical issue of self-experimentation was raised by his bold experiment and many aspects of his investigations and conclusions have been criticized, Head undoubtedly contributed important clinical lessons to neurology. Arguably, Henry Head's greatest contribution was the realization that the neurological portion of the sensory examination was anything but straightforward.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".