E‐model based comparison of multiple description coding and layered coding in packet networks
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Bibliographic record
Abstract
Abstract We examine the performance of multiple description coding (MDC) with and without the use of automatic repeat request (ARQ) protocols for packet network communication, in comparison with layered coding (LC). The rate‐distortion lower bound of MDC and LC are incorporated into an E‐model based performance measure, which accounts for the additional costs of excess rates and delay incurred from using ARQ. The results show that the relative merits of the schemes depend on the values of the packet loss rates and round‐trip‐time (RTT). LC is superior for small RTT and unaided MDC is superior for large RTT. For moderate RTT, LC is preferred for small packet loss rates and MDC aided by ARQ is preferred for large packet loss rates. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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