Vys: A Protocol for Commensal Fast Transient Searches and Data Processing at the Very Large Array
Bibliographic record
Abstract
We describe a new protocol deployed at the National Radio Astronomy Observatory’s Karl G. Jansky Very Large Array (VLA) to support the distribution of data in support of commensal data analysis. The protocol, vys, is designed to provide access to a high time resolution data stream while a primary observation continues with the typical (lower) time resolution data stream. This form of dual time resolution, commensal observing has been implemented to enable the search for millisecond astrophysical transient events by a new, dedicated compute cluster located at the VLA. The fast transient detection system, realfast, performs real-time analysis in situ to detect events of interest and record relatively short duration data “cut-outs” of those events. By selectively recording high time resolution data, provided by vys at rates of up to 1.4[Formula: see text]GB[Formula: see text]s[Formula: see text], realfast will reduce the recorded data volume by an estimated factor of up to 1000. This makes it possible to search for transients commensally in a high data rate stream over the thousands of hours needed to find the rarest events.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.023 |
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".