Bibliographic record
Abstract
In the small industrial town of Hamilton, Ontario, a room of high school students listened attentively as their physics teacher described the classic Bohr model of the atom. It was 1963. After just a few minutes, the lecture was disrupted by muffled sniggering from a student near the front of the class. Clifford M. Will. A voracious consumer of popular science, Clifford Will—now a professor of physics at Washington University in St. Louis and 2007 inductee to the National Academy of Sciences—had read enough to know that the Bohr model was obsolete. “I couldn't keep myself from laughing,” Will recalls. However, rather than becoming angry, the teacher issued a challenge: Will had one week to deliver a lecture on the modern theory of atomic structure. Since his first lecture in a small Canadian classroom in the early 1960s, Will has spent more than four decades describing experimental tests of Einstein's theory of gravity, better known as general relativity, to lay and scientific audiences around the world. His 1986 book, Was Einstein Right? (1), landed on the New York Times Book Review's best books list and has been translated into nearly a dozen languages. Today, Will is no stranger to the podium. As a teen, Will aspired to many professions, but none of them involved theoretical physics. During high school, he took drafting classes, and architect emerged high on the list of potential future careers. “I grew up in a working class family, so the idea of moving ahead in the world was certainly attractive. And besides, I thought architects made lots of money,” he admits with a laugh. However, all of that had changed by his senior year, when a patient and inspirational physics teacher by the name of Paul Simpson helped channel Will's restlessness and issued the challenge that …
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.141 | 0.070 |
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".