Bibliographic record
Abstract
: Isadore Max Tarlov (1905-1977) is primarily remembered for his 1938 description of the eponymous perineural "Tarlov cyst." However, during his long career as a neurosurgeon and researcher, he was responsible for many other observations and inventions that influenced the development of neurosurgery in the 20th century. While studying at Johns Hopkins Medical School he was acquainted with Walter Dandy, and he became the first resident to study under Wilder Penfield at the newly formed Montreal Neurological Institute. He made many novel observations about peripheral and cranial nerve anatomy, pioneered nerve anastomosis and grafting techniques, and introduced the concept of fibrin glue. He developed an animal model of spinal cord injury and used it to establish for the first time that functional neurological reserve is proportional to rapidity of injury, because gradual onset of compression is better tolerated by neural tissue than acute compression. He was the first to describe the use of the knee-chest position for lumbar spine surgery to minimize increases in epidural venous pressure due to abdominal compression. Finally, near the end of his career, he published a collection of thoughtful, philosophical essays entitled The Principle of Parsimony in Medicine and Other Essays, in which he advocated for a humanistic and restrained approach to medical practice. In this article, we discuss the contributions of Tarlov to the field of neurosurgery, including many of his lesser-known accomplishments that have become part of neurosurgery's collective legacy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".