Bibliographic record
Abstract
of the American Mathematical SocietyAll of us, wherever we are, can celebrate together here in this issue of Notices the San Diego Joint Mathematics Meetings.Our lecture sampler includes for the first time the AMS-MAA-SIAM Hrabowski-Gates-Tapia-McBay Lecture, this year by Talithia Williams on the new PBS series NOVA Wonders.After the sampler, other articles describe modeling the heart, Dürer's unfolding problem (which remains open), gerrymandering after the fall Supreme Court decision, a story for Congress about how geometry has advanced MRI, "My Father André Weil" (2018 is the 20th anniversary of his death), and a profile on Donald Knuth and native script by former Notices Senior Writer and Deputy Editor Allyn Jackson.It is with some sadness and much appreciation that I report that Allyn, after over 30 years at the AMS, is moving on to other activities.The editors have found it an honor and privilege to work with her and wish her every happiness in whatever lies ahead; don't miss the appreciation on page 58.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".