On the design of efficient video-on-demand broadcast schedules
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
In order to address the scalability problems of video-on-demand systems, several periodic broadcast schemes have been proposed that partition a video into segments and repetitively broadcast each segment on a separate channel. A new scheme is presented for the bandwidth-efficient periodic broadcast of video. The proposed scheme determines the segment sizes and their corresponding channel bandwidths as a result of a non-linear optimization problem which minimizes the total required bandwidth for the broadcast. The new scheme outperforms the existing schemes in terms of bandwidth demands while it also decouples the playout latency from the number of available channels. Further analysis reveals that its asymptotic bandwidth requirements exactly match the asymptotic bandwidth requirements reported for poly-harmonic broadcasting.
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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 | 0.001 |
| 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) | 0.001 | 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