Developing Autonomic Feedback Control for Heterogeneous Systems Using Cascaded Controllers
Why this work is in the frame
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Bibliographic record
Abstract
The motivation of the work is based on the static use of reference point values in dynamic feedback control systems that are based on control theoretic techniques. Reference point values are threshold values that values of attributes characterizing system behavior can be compared to. The result of the comparison is used to adjust the tuning parameter of the system being controlled. If the entity being controlled is a server then the best choice for the reference value may depend on many factors such as the required processing times, the machine speed that the server is executing on, etc. This paper illustrates an approach to automatically change the reference value for different server hardware. Comparisons are made between the approach proposed in this paper and other dynamic feedback control approaches. Results show that the proposed approach outperforms the other dynamic feedback control approaches
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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 it