Dynamic service reconfiguration and migration in the Kea kernel
Bibliographic record
Abstract
Kea is a new operating system developed for experimentation with kernel structuring, configuration and specialization. There are several features of Kea's design that make the investigation of these issues practical. Firstly it supports fine-grain decomposition of kernel services, the components of which communicate using inter-domain calls. This communication mechanism forms the backbone of Kea's reconfigurability, as services can be located in separate domains, for development or debugging purposes, and then dynamically migrated into a common domain, or into the kernel itself, transparently to the users of the service. The inter-domain calls are automatically optimized to procedure calls as appropriate. The service hierarchy can also be dynamically reconfigured through replacement, or the layering of new services, either on a system wide or application specific basis. We describe these features, and discuss the results from several experiments that demonstrate the practicality and performance advantages of Kea's design.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".