Memories of David S. Chapman (1929 –2023)
Bibliographic record
Abstract
CHAPMAN, D.S. was born on August 31, 1942 on Vancouver, Canada. Son of Margaret and Harry Chapman and part of a large family with 4 more siblings. Married with Inga Hahn, who know at University British Columbia. David Chapman passed away unexpectedly on 10 March in Vancouver, British Columbia. Dave was an extraordinary researcher, teacher, mentor, and administrator. He loved to demonstrate what could be accomplished using the back of an envelope, a pencil, and a little brainpower. His research in geophysics spanned the globe, using measurements of temperature to understand topics from plate tectonics to climate change. His teaching, from equations on napkins discussed during coffee breaks to his classroom demonstrations to his exemplary example of ethical behavior, left an indelible mark on thousands of students and colleagues around the world. As Dean of the Graduate School he engineered changes to programs to the benefit of all students. We all will miss Dave and his ever upbeat attitude towards problems large and small. In honor him, the UTAH University create the Chapman Found supports unique educational and research opportunities for both graduate and undergraduate students. He receive too the Rosenblatt Prize at UTAH University.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 0.013 |
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".