On message recognition protocols: recoverability and explicit confirmation
Bibliographic record
Abstract
We look at message recognition protocols (MRPs) and prove that there is a one-to-one correspondence between stateless non-interactive MRPs and digital signature schemes. Next, we examine the Jane Doe protocol and note its inability to recover in case of a certain adversarial disruption. We propose a variant of this protocol which is equipped with a resynchronisation technique that allows users to resynchronise whenever they wish. Moreover, we propose another protocol which self-recovers in case of an intrusion. This protocol incorporates the resynchronisation technique within itself. Further, we enumerate all possible attacks against this protocol and show that none of the attacks can occur. Finally, we prove the security of the new protocol and its ability to self-recover once the disruption has stopped. Finally, we propose an MRP which provides explicit confirmation to the sender on whether or not the message was accepted by the receiver.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.004 | 0.026 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".