Evaluating and Enhancing Candidate Clocking Systems for CHIME/FRB VLBI\n Outriggers
Bibliographic record
Abstract
As the Canadian Hydrogen Intensity Mapping Experiment (CHIME) has become the\nleading instrument for detecting Fast Radio Bursts (FRBs), CHIME/FRB Outriggers\nwill use very-long-baseline interferometry (VLBI) to localize FRBs with\nmilliarcsecond precision. The CHIME site uses a passive hydrogen maser\nfrequency standard in order to minimize localization errors due to clock delay.\nHowever, not all outrigger stations will have access to a maser. This report\npresents techniques used to evaluate clocks for use at outrigger sites without\na maser. More importantly, the resulting algorithm provides calibration methods\nfor clocks that do not initially meet the stability requirements for VLBI, thus\nallowing CHIME/FRB Outriggers to remain true to the goal of having\nmilliarcsecond precision.\n
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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 | 0.005 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".