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
Current leader-based Byzantine fault-tolerant (BFT) protocols aim to improve the efficiency for achieving consensus while tolerating failures; however, Byzantine servers are able to repeatedly impair BFT systems as faulty servers launch attacks without costs. In this paper, leveraging Proof-of-Work and Raft, we propose a new BFT consensus protocol called Prosecutor that dynamically penalizes suspected faulty behavior and suppresses Byzantine servers over time. Prosecutor obstructs Byzantine servers from being elected in leader election by imposing hash computation on new election campaigns. Furthermore, Prosecutor applies message authentication to achieve secure log replication and maintains a similar message-passing scheme as Raft. The evaluation results show that the penalization mechanism progressively suppresses and marginalizes Byzantine servers if they repeatedly launch malicious attacks.
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