Bibliographic record
Abstract
Edited by Scott Stull , sstull@alum.mit.edu , EducAide Software, Richmond, CA 94806; associate editors Debra Kerr , State College Area School District, Tyrone, PA 16686, and Jane Lataille , Windsor, CT 06095-1775 Problems 1–9, 11, 13, 14, and 16–19 were submitted by Richard Evans and Judy Buck, Plymouth State College, Plymouth, NH 03264. Problems 10, 12, 15, and 20–30 came from Elaine Simmt's and Florence Glanfield's Mathematics Majors and Minors, University of Alberta, Edmonton, AB T6G 2E8. Problem 31 was contributed by Dipendra Bhattacharya, Clarion University of Pennsylvania, Clarion, PA 16214-1232. Problems 9 and 11 were published in “Brain Bogglers,” by Michael Stueben, in the July 1987 issue and the January 1985 issue, respectively, of Discover magazine.
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 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".