Bibliographic record
Abstract
Let $\mathcal D$ be a strongly self-absorbing $\mathrm{C}^*$-algebra. Given any separable $\mathrm{C}^*$-algebra $A$, our two main results assert the following. If $A$ is $\mathcal D$-stable, then the corona algebra of $A$ is $\mathcal D$-saturated, i.e., $\mathcal D$ embeds unitally into the relative commutant of every separable $\mathrm{C}^*$-subalgebra. Conversely, assuming that the stable corona of $A$ is separably $\mathcal D$-stable, we prove that $A$ is $\mathcal D$-stable. This generalizes recent work by the first-named author on the structure of the Calkin algebra. As an immediate corollary, it follows that the multiplier algebra of a separable $\mathcal D$-stable $\mathrm{C}^*$-algebra is separably $\mathcal D$-stable. Appropriate versions of the aforementioned results are also obtained when $A$ is not necessarily separable. The article ends with some non-trivial applications.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".