No woman alone: Dorothy Russell’s legacy to neurosurgery
Bibliographic record
Abstract
Dorothy Russell's contributions to neuropathology are pivotal in the evolution of modern neurosurgery. In an era preferential to men in medicine, she entered the second medical school class to include women at the London Hospital Medical College in 1919. In the laboratory of Hubert Turnbull, she met Hugh Cairns, who would become her professional neurosurgeon-neuropathologist partner. In 1929, arriving at McGill's Royal Victoria Hospital in Montreal, where Wilder Penfield and William Cone had just begun a neurosurgical service, Russell elucidated the origin and activity of microglia. Returning to London, Russell continued to work closely with Cairns for many years. Along with J. O. W. Bland, she became the first to culture gliomas and meningiomas. Her work on the effects of and fatality rates associated with head injuries among soldiers during World War II led to the initiation of helmet requirements for motorcyclists. Her textbook, Pathology of the Tumours of the Nervous System, written with Lucien Rubinstein, is considered a landmark text in neurosurgery, neuropathology, and neurooncology. Honored by Penfield and Cone as their first neurosurgery research fellow, Russell was considered a favorite of the Montreal Neurological Institute. Dorothy Russell's extraordinary career elucidating the mysteries of neurosurgical pathology has made an enduring mark on neurosurgery.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".