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
The recent applications in communications are required to meet low-latency transmission with high traffic rates and reliabilities. From the latency point of view, most of the state-of-the-art techniques consider the average latency which does not directly apply to delay-sensitive scenarios. In this paper, we propose a novel approach to tackle the scheduling problem by directly addressing the max-delay constraint; this is an NP-hard problem. Our main contributions are first, proposing the Super State Monte-Carlo Tree Search (SS-MCTS) as a version of regular MCTS modified for large-scale probabilistic environments with less computational complexity, and second, addressing the scheduling problem with maximum delay constraint on flows. Our numerical results demonstrate that the proposed approach significantly improves the packet delivery rate while meeting the maximum delay constraint in large-scale scenarios compared to the state-of-the-art technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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