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
Docker has been widely adopted as a platform solution for microservice. As the popularity of microservice increases, the importance of fine-tuning the efficiency of resource management in the Docker platform also increases. While Docker’s out-of-box resource management solution provides some generic management capability, more work is required to improve resource utilization and enforce Service Level Agreement (SLA) for critical services. In this research, an efficient Docker resource management scheme, called Adaptive SLA Enforcement, is designed and implemented. For the sake of comparison, we also study and implement three simpler schemes: 1) Fixed Number of Containers, 2) Dynamic Resource Management without SLA Enforcement, 3) Strict SLA Enforcement. We found that the Adaptive SLA Enforcement scheme can deliver efficient resource management with SLA enforcement, thus successfully addressing the deficiencies of the other three schemes.
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 | 0.000 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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