Server-based smoothing of variable bit-rate streams
Why this work is in the frame
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Bibliographic record
Abstract
We introduce an algorithm that uses buffer space available at the server for smoothing disk transfers of variable bit-rate streams. Previous smoothing techniques prefetched stream data into the client buffer space, instead. However, emergence of personal computing devices with widely different hardware configurations means that we should not always assume abundance of resources at the client side. The new algorithm is shown to have optimal smoothing effect under the specified constraints. We incorporate it into a prototype server, and demonstrate significant increase in the number of streams concurrently supported at different system scales. We also extend our algorithm for striping variable bit-rate streams on heterogeneous disks. High bandwidth utilization is achieved across all the different disks, which leads to server throughput improved by several factors at high loads.
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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