Nobel prizes for computational science [The Last Word]
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
By the time you read this column, the Royal Swedish Academy of Sciences will have announced the recipients of this year's Nobel Prizes in Physiology or Medicine, Physics, and Chemistry . The chances are good that computational science contributed to some of the prize-winning work. What tours de force of computational science deserve future Nobels? At the top of my list in medicine is the Human Genome Project. However, given Alfred Nobel's stipulation that no more than three people share a prize, the vast project could miss out. Particle physics discoveries typically involve Herculean feats of number crunching. The Sudbury Neutrino Observatory's (SNO) confirmation in 2001 that neutrinos oscillate in flavor merits a physics prize, a share of which would presumably go to SNO's director, Art McDonald. In chemistry, I favor honoring Harvard's Martin Karplus for pioneering the use of molecular dynamics simulations to elucidate the behavior of proteins and other biomolecules. By the time you read this column, you'll know if any of my predictions came true.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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