A high sensitivity VDFLL utilizing precise satellite orbit/clock and ionospheric products
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
In the VDFLL, the ranging errors will degrade the positioning accuracy as well as the tracking performances. In the paper, a new VDFLL tracking loop minimizing the ranging error by utilizing precise satellite orbit/clock and ionospheric products has been proposed. Unlike the conventional VDFLL, which treats all the measurement errors as zero-mean Gaussian noise with a high variance, the new VDFLL will first reduce the biases using precise satellite orbit/clock and atmospheric delay data and then assign a lower measurement error variance in the EKF. With reduced ranging errors, the positioning accuracy is improved more than 30% and the ranging error and tracking sensitivity of tracking loop are improved by around 3dB.
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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