A Stateful Approach to Generate Synthetic Events from Kernel Traces
Why this work is in the frame
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Bibliographic record
Abstract
We propose a generic synthetic event generator from kernel trace events. The proposed method makes use of patterns of system states and environment-independent semantic events rather than platform-specific raw events. This method can be applied to different kernel and user level trace formats. We use a state model to store intermediate states and events. This stateful method supports partial trace abstraction and enables users to seek and navigate through the trace events and to abstract out the desired part. Since it uses the current and previous values of the system states and has more knowledge of the underlying system execution, it can generate a wide range of synthetic events. One of the obvious applications of this method is the identification of system faults and problems that will appear later in this paper. We will discuss the architecture of the method, its implementation, and the performance results.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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