Supporting hot-swappable components for system software
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
Summary form only given. A hot-swappable component is one that can be replaced with a new or different implementation while the system is running and actively using the component. For example, a component of a TCP/IP protocol stack, when hot-swappable, can be replaced (perhaps to handle new denial-of-service attacks or improve performance), without disturbing existing network connections. The capability to swap components offers a number of potential advantages such as: online upgrades for high availability systems, improved performance due to dynamic adaptability and simplified software structures by allowing distinct policy and implementation options to be implemented in separate components (rather than as a single monolithic component) and dynamically swapped as needed. In order to hot-swap a component, it is necessary to (i) instantiate a replacement component; (ii) establish a quiescent state in which the component is temporarily idle; (iii) transfer state from the old component to the new component; (iv) swap the new component for the old; and (v) deallocate the old component.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it