Founders of Pediatric Pathology: Marie Valdés-Dapena
Bibliographic record
Abstract
Marie (‘‘Molly’’) Valdes-Dapena (Fig. 1) (nee Brown) was born on July 14, 1921, in Pottsville, PA. After primary education she attended Immaculata College, near Philadelphia, majoring in Biology and graduating in 1941. She entered Temple University School of Medicine (TUSM) in Philadelphia in 1941 and received her MD in 1944. Molly was a rotating intern and a resident in Pathology (1944–49) in the Philadelphia General Hospital (PGH). She was licensed to practice in 1945 and certified by the American Board of Pathology (ABP) in 1949. She worked the next 2 years as Assistant Pathologist at the FitzgeraldMercy Hospital (‘‘Fitz’’) in Derby, PA. In 1951, she moved to the Women’s Medical College Hospital (WMCH) of Philadelphia (later the Medical College of Pennsylvania) as Pathologist and later as Director of Laboratories. While at WMCH, Molly also held appointments at the University of Pennsylvania School of Medicine and Dentistry as Instructor of Pathology. She rose through the ranks to Associate Professor before beginning her new professional life and ‘‘the apprenticeship’’ in Pediatric Pathology at St Christopher’s Hospital for Children in Philadelphia (‘‘St Chris’’). At ‘‘St Chris and TUSM, Dr Waldo E. Nelson was the Chief of Pediatrics. Other prominent staff were Dr Angelo DiGeorge (Di-
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.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.009 |
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".