Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Largely because of the advances of the Civil Rights movement in the mid-20th century, an increasing number of African-Americans have had the opportunity to become physicians and enter the distinguished field of neurosurgery. Many have made the most of this opportunity, becoming prominent in both academics and private practice. Unfortunately, the details regarding the first African-American neurosurgeon, Clarence Sumner Greene, Sr., have remained in relative obscurity. Born on December 26, 1901 in Washington, D.C., Dr. Greene received his M.D. from the Howard University College of Medicine with distinction in 1936. After 7 years of general surgery residency and 4 years as a professor of surgery at Howard University, he was granted the opportunity by the legendary Wilder G. Penfield to train in neurosurgery at the world-renowned Montreal Neurological Institute from 1947 to 1949. Receiving high praise from Dr. Penfield, Dr. Greene became the first African-American certified by the American Board of Neurological Surgery on October 22, 1953. Subsequently, he was appointed as chair of neurosurgery at Howard University, where he successfully treated intracranial aneurysms, brain tumors, and herniated intervertebral discs until his tragic death in 1957. The diligence and perseverance of Clarence Sumner Greene, Sr., M.D., D.D.S., F.A.C.S. enabled him to overcome incredible odds to become the first African-American neurosurgeon, trained by Dr. Penfield at the Montreal Neurological Institute. A true pioneer, his achievements have opened the door for subsequent African-Americans to enhance the field of neurosurgery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it