Bibliographic record
Abstract
Zena Werb was born in Bergenbelsen, Germany to Polish Jewish parents. As a post-war refugee, with her family she moved from Wroclaw, Poland to Milan, Italy. From there they immigrated to Canada, first to Saskatchewan and then to southern Ontario, where Zena grew up on a farm. She went to the University of Toronto, where she read Honours Biochemistry, receiving a BSc in 1966. Studying with the late Professor Zanvil A. Cohn, Zena received her PhD in cell biology from The Rockefeller University, New York. Her post-doctoral work was at the Strangeways Research Laboratory in Cambridge, UK. After one year on the faculty of Dartmouth Medical School in Hanover, New Hampshire, she joined the University of California, San Francisco, as an Assistant Professor in the Laboratory of Radiobiology. She is currently Professor and Vice-Chair of Anatomy and a member of the Program in Biological Sciences and Biomedical Sciences Program at the University of California, San Francisco. Zena's research is on the roles of matrix metalloproteinases in normal and pathological tissues, concentrating on mouse models of bone and mammary gland development. She has demonstrated the importance of proteolysis as a mechanism of altering extracellular signaling. She has shown that remodeling of the extracellular matrix and the cellular microenvironment by stromal and inflammatory cells contributes to development of tumors as aberrant organs.
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 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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".