Bibliographic record
Abstract
In the context of the IEEE 1588 Precision Time Protocol (PTP), estimating the delay's bias is a problem that appears in both one-way (using transparent devices) or two-way message exchange mechanisms.For estimating the offset via the two-way message exchange mechanism, it is usually being assumed that the expected value of delays in forward and reverse directions are equal with each other.However this is not a realistic assumption for packet-based wide area networks, where delays in down-link and up-link directions may have a significant difference.In this work we propose a solution to estimate the random delay's bias and improve the synchronization accuracy of IEEE 1588.Our method is easy to implement and is compatible with the current version of the protocol.We compared our results with no bias correction and the Boot-strap method.In addition to the improvement in synchronization accuracy, our method allows us to update the slave clock recursively.The proposed method works well even in the presence of large frequency offsets and can also be implemented by using different filters. List of FiguresAccuracy and stability of a clock oscillator [3] . . . . . . . . . . . . .
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".