RFI Issues for the Next Generation Very Large Array (ngVLA)
Bibliographic record
Abstract
Building on the remarkable success of the VLA, VLBA, and ALMA, NRAO is planning a large collecting area interferometer which will replace the VLA and VLBA - the next generation Very Large Array (ngVLA) [1]. For many of the same reasons that the VLA was constructed where it was (fraction of sky visible, quality of site, accessibility, etc.), the core and bulk of the collecting area of the ngVLA will be on the Plains of San Agustin, near where the center of the current VLA is. Despite the general quality of the site, RFI is nearly ubiquitous, especially at frequencies below 2 GHz, and the spectrum is getting worse with time, as experienced in other areas across the world. Also, because of the spatial resolution needed to satisfy science requirements, antennas will be spread across the U.S., Canada, and northern Mexico, and so be in different RFI environments (see Figure 1 for locations of antennas in the current design) [2], [3].
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.012 |
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".