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
We consider the problem of gossiping when dynamic node crashes are controlled by adaptive adversaries. We develop gossiping algorithms which are efficient with respect to both the time and communication measured as the number of point-to-point messages. If the adversary is allowed to fail up to $t$ nodes, among the total of $n$, where additionally $n-t=\Omega(n/\textpolylog n)$, then one among our algorithms completes gossiping in time $\cO(\log^2 t)$ and with $\cO(n\text polylog t)$ messages. We prove a lower bound which states that the time has to be at least $\Omega\Big(\frac\log n\log(n\log n)-\log t\Big)$ if the communication is restricted to be $\cO(n\text polylog n)$.We also show that one can solve efficiently a more demanding consensus problem with crash failures by resorting to one of our gossiping algorithms. If the adversary is allowed to fail $t$ nodes, where $n-t=\Omega(n/\textpolylog n)$, we obtain a time-optimal solution that is away from the communication optimality by at most a polylogarithmic factor.
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 | 0.001 |
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