Bibliographic record
Abstract
Abstract In this paper, we show that the SPARK software of the Natural Resources Canada (NRCan) with their DCR (Decoupled Clock Rapid) products can be used to generate the PPP-AR continuous batch clock solutions of multiple days, which we use to build frequency transfer links between two remotely located GPS receivers. The reliability and confidence in forming the long-term frequency transfer links have been improved compared to Jian et al (2023 Metrologia 60 065002). We compare the SPARK PPP-AR links to an optical fiber and TWSTFT links for hundreds of days. The ~500-day-long comparisons with TWSTFT show no frequency bias for continental and cross-continental links. Frequency transfer links formed using the SPARK solutions have uncertainty of 1 × 10 − 15 / T , where T is in days, without reaching the noise floor, a critical requirement for comparing optical frequency standards and for the redefinition of the SI second. The short latency of the NRCan DCR products enables the quick availability of the PPP-AR links presented in this paper marking it particularly relevant for time sensitive applications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.018 | 0.007 |
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".