Remote time and frequency calibration with holdover traceability from a new treatment of non-white noise in rubidium clocks
Bibliographic record
Abstract
A new method of uncertainty analysis for non-white noise is presented and used to evaluate traceable holdover capabilities of a new NRC system for time and frequency dissemination to remote rubidium-cell (Rb) clocks. As in many similar systems, these remote clocks are disciplined to track UTC using the Global Positioning System and the common view time transfer method. When disciplining data is unavailable, we extend traceability into this holdover period with evaluations of uncertainty from the measurements of the Rb clock’s non-white noise: modelled, matched, and simply presented as a time dependent dispersion in Monte Carlo simulations. This leads to improved simplicity, reliability and economy for the new method, with a post processed standard uncertainty down to 6 ns when disciplined, with a holdover period of t seconds introducing an uncertainty component of 1.82 × 10 −3 t nanoseconds (combined standard uncertainty of 160 ns for a 24 h holdover).
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".