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
Network coding has emerged as a promising approach that enables reliable and efficient end-to-end transmissions in lossy wireless mesh networks. Existing protocols have demonstrated its resilience to packet losses, as well as the ability to integrate naturally with multipath opportunistic routing. However, these heuristics do not take into account the inherent resource competition in wireless networks, thereby compromising the coding advantages. In this paper, we take a game-theoretic perspective towards optimized resource allocation for network coding based unicast protocols. We design decentralized mechanisms that achieve better efficiency-fairness tradeoff, for both cooperative and selfish users. Our framework features a modularized optimization of two subproblems: the multipath routing of coded information flows for each player, and the broadcast and coding rate allocation among competing players. We have implemented the framework on a wireless emulation testbed and demonstrated its high performance in terms of throughput and fairness.
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 | 0.000 |
| 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