Bibliographic record
Abstract
An interview in three sessions, in June 2001, with Wilhelmus Anthonius Josephus (Wim) Luxemburg, professor of mathematics, emeritus, in the Division of Physics, Mathematics, and Astronomy. Dr. Luxemburg received his BA. from the University of Leiden (1950) and his doctorate from the Delft Institute of Technoloy (1955). He and his wife emigrated to Canada, first to Kingston and then to the University of Toronto as a postdoc with Israel Halperin. In 1958, he came to Caltech as an assistant professor in the mathematics department, at the invitation of H. Frederic Bohnenblust. He became a full professor in 1962, served as executive officer for mathematics from 1970 to 1985, and became professor emeritus in 2000. He recalls his childhood during the First and Second World Wars in Delft, and the deprivations of the postwar period. Discusses his doctorate with Adriaan C. Zaanen at Delft Institute of Technology, on Banach function spaces. Attends 1954 International Congress of Mathematicians in Amsterdam. Invitation from Halperin to come to Canada. His postdoc at the University of Toronto. Travels in Canada. Invited to join Caltech faculty by Bohnenblust. He comments on the development of mathematics at Caltech, including expansion of applied mathematics and joint appointments with engineering division. Discusses Olga Taussky-Todd as Caltech’s first woman full professor; Caltech’s abortive attempt to merge with Immaculate Heart College; his membership on Aims and Goals Committee. Recollections of presidencies of Harold Brown, Marvin L. Goldberger, Thomas E. Everhart; support of mathematics by then-current President David Baltimore; travels and life as emeritus professor.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.051 | 0.014 |
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".