Bibliographic record
Abstract
I cannot imagine a single neurosurgeon who would not enjoy this book.It is certainly true that much has been written about Harvey Cushing, and Michael Bliss's biography, "Harvey Cushing: A Life in Surgery" published in 2005 provides one of the best reads regarding his life.However, "The Legacy of Harvey Cushing", by Cohen-Gadol and Spencer, affords a totally different experience.Harvey Cushing revered by many as the father of neurosurgery, is presented in a visually stunning manner.They provide an intimate portrait of Harvey Cushing's neurosurgical abilities using a case-based approach, aided by the original patient records, spectacular photographs of patients and their pathology, and a fantastic collection of his diagrams.These patient stories clearly illustrates his tremendous medical skills, exceptional ability to localize disease within the nervous system, and willingness, matched by skill, to expand the scope of neurosurgical possibilities.Finally, the book ends with a wonderful collection of photographs depicting Dr. Cushing at work.These photographs, as well as those of his patients, are truly magnificent.Harvey Cushing lived at the beginning of the 20th century at a time when diagnostic imaging, surgical equipment and anesthetic techniques were primitive by today's standards.He stands out for the remarkable advancement of neurosurgery that occurred through his efforts.Prior to Harvey Cushing, the mortality of craniotomy for patients with brain tumors was over 50%.Harvey Cushing reduced this to 10%.In addition, while he wrote seminal works on many neurosurgical domains, he also won a Pulitzer Prize in 1926 for a biography of Sir William Osier.His incredible surgical successes were punctuated by honest descriptions of his
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.800 | 0.722 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".