Bibliographic record
Abstract
SAMSI), as well as the Banff International Research Station (BIRS) in Canada that is supported by Canada, the US, and Mexico.Links to the pages of all the institutes can be found at http://mathinstitutes.org/.All these institutes provide a valuable and accessible resource for organizing and attending workshops and other programs in linear algebra.In this article, we emphasize opportunities to organize or participate in week-long research workshops offered by these institutes.Participants are typically provided with support for local expenses and in some cases travel funds are available.Although it is generally expected that one or more of the organizers be US citizens (and in the case of BIRS, one or more be Canadian citizens), participants are usually invited from all over the world.In addition to workshops, many of the institutes have many other programs for researchers, graduate students, undergraduates, industry, and the public; we will only briefly and partially mention such programs in this article.Any of these programs can be highly stimulating to research.While all the institutes offer workshops, there are substantial differences in suitable topics for proposals.Some of the institutes have a particular institutional focus (for example, SAMSI emphasizes statistics) or a different theme each year with most workshops related to the theme.Also, many of the institutes have some form of university membership and some special programs are restricted to faculty and students at member universities.The websites for AIM, IMA, IPAM, MSRI, SAMSI and BIRS all make it easy to find out how to propose activities; AIM, IPAM, MSRI and BIRS have links for proposers on their main page; IMA and SAMSI have such links on the "Programs" page.Many of the institutes have been supportive of linear algebra and offer excellent access to research support.IMA, AIM, and BIRS are of particular interest to ILAS members.IMA hosted a linear algebra year in 1991-1992 organized by R.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.542 | 0.320 |
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".