Looking at a Painting with a Mathematical Eye.
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
It was at one of the U.K. Association of Teachers of Mathematics meetings, probably in the early or mid-1970s, that I first met David Wheeler. I am not sure how it came about that he always supported my interest in mathematics and the visual arts, but it was certainly he who gave me my first opportunity to give a course in this area when he invited me to teach a summer session for teachers at Concordia University in Montreal. He gave me free reign and much encouragement, but occasionally this came with a sprinkling of constructive suggestions and a twinkle in his eye. Unfortunately, lam not able to locate the correspondence dealing with the session on *mathematizing ' that he, Eric Love, John Trivett and I carried on as part of the preparation for our session at ICME IV in San Francisco in 1980. I do recall though that I was not successful in convincing him that I really did not fully understand what was meant by that term. But he assured me that I did it all the time, and it is true I did manage to give a talk on 'mathematizing with apiece of paper'. [1] From the launch ofFLM in 1980 until issue 50 when he retired as editor, David was concerned with the visual aspects of the journal. A few quotations from some of his letters to me will indicate this:
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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