Synopsis of a presentation to the American Association of Physics Teachers,
Bibliographic record
Abstract
In 1982 I was privileged to address you at your annual meeting in London, Ontario. At that time I discussed how classical physics such as properties of matter had tended to be overlooked in our teaching of physics in favour of some of the apparently more glamorous solid-state nuclear physics systems etc. At the end of the lecture I was approached to ask if some of the material on the applied physics of instruments I presented was available in written form. The answer was no but the question stimulated me to plan a book to be entitled "Delightful Instruments " and "Exciting Moments in Applied Science". The idea being that I would describe some of the more modern instruments that embody- exciting aspects of physics. I am afraid that I have only produced one chapter of the book which I have titled "Harmonious Rocks and Infinite Coastlines " in which I discuss some rather novel applications of Fourier Analysis and fractal geometry. I have brought a copy of this chapter along for you to inspect. The reason the project has not developed further is that my involvement with fractal dimensions has escalated to the point where
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.128 | 0.075 |
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".