On messy broadcasting in directed hyper-cylinder graphs
Why this work is in the frame
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Bibliographic record
Abstract
In classical broadcast models, information is disseminated in synchronous rounds under the constant communication time model, where a node informs only one neighbour per time unit – also known as the processor-bound model. These models assume either a leader coordinates actions or each node has a set of coordinated actions (or can compute them) optimized for each originator. In the latter case, nodes must have enough storage, processing power, and the ability to determine the originator. This assumption is not always ideal, and a broadcast model based on local knowledge can be more practical. Messy models address this by removing the leader, starting time knowledge, and originator information, leaving each node with only local knowledge. A new class of graphs, Hyper-cylinders, inspired by broadcast behaviour and the common use of Torus, Grid, and Hypercube structures, is introduced. This paper explores the broadcast time and optimum schemes for Hyper-cylinders under Messy models, deriving known theorems, including those for directed Torus and undirected Hypercube, as corollaries. Additionally, it provides corollary results for subtypes like Grid and Spider Web Graphs.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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