Phanor L. Perot Jr.: South Carolina’s father of academic neurosurgery
Bibliographic record
Abstract
Phanor Leonidas Perot Jr., MD, PhD (1928-2011), was a gifted educator and pioneer of academic neurosurgery in South Carolina. As neurosurgical resident and then as a junior faculty member at the Montreal Neurological Institute, he advanced understandings of both epilepsy and spinal cord injury under Wilder Penfield, William Cone, and Theodore Rasmussen. In 1968, he moved to Charleston to lead neurosurgery. From his time spent with master physicians such as Isidor Ravdin and Wilder Penfield, Perot himself became "the ultimate teacher." His research spanned the fields of epilepsy to torticollis to spinal trauma, focusing the most on the basic pathophysiology of spinal cord damage elucidated through somatosensory evoked potentials. His research was distinguished by generous grant funding. By the time he stepped down as chairman in 1997, the division of neurosurgery had become a department and he had served as president of the American Academy of Neurological Surgery and the Society of Neurological Surgeons. Perot taught prolifically at the bedside, and considered the residency program at the Medical University of South Carolina his greatest achievement. Although Dr. Perot never fully retired, he also enjoyed active hobbies of fly-fishing, traveling, and hunting, until his death on February 2, 2011. He influenced many and earned his role in history as the father of academic neurosurgery in South Carolina.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".