Maud L. Menten: Pioneering Physician and Biochemist
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
Dr. Maud Leanora Menten, an esteemed Canadian physician, biochemist, and organic chemist, conducted a wide range of valuable biochemistry research for over 40 years, making groundbreaking discoveries about cancer treatments, enzyme kinematics, anesthesia medicine, bacterial toxins, vitamin deficiencies, hematology, and histochemistry. Menten demonstrated intense perseverance and tenacity in her education, defying societal norms to not only become one of the first Canadian women to earn a research-intensive Doctor of Medicine (MD) degree, but to also be one of the first to earn a PhD. Although she was restricted in her work in Canada, she moved to the U.S. and published an estimated 100 research studies over her career. She is most well known for her work with Dr. Leonor Michaelis, with whom she created the Michaelis-Menten equation for the relationship between reaction rate and enzyme-substrate concentration. However, she conducted many other noteworthy research projects, such as using radium bromide for cancer treatment in rats and using electrophoretic mobility to study human hemoglobin, which allowed for a more advanced protein analysis. Her research in hemoglobin preceded the findings of Linus Pauling by several years, however, he is often the only one credited for this work. After her death, the extent and depth of her work was better understood and appreciated by many, and she was recognized by her alma mater, the University of Toronto, and her former workplace, the University of Pittsburgh. She was also posthumously inducted into the Canadian Medical Hall of Fame.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it