The expanded very large array
Bibliographic record
Abstract
The Expanded Very Large Array (EVLA) is an international project to improve the scientific capabilities of the Very Large Array (VLA), an aperture synthesis radio telescope consisting of 27, 25-meter diameter antennas distributed in a Y-shaped configuration on the Plains of San Augustin in west-central New Mexico. The EVLA's major science themes include measuring the strength and topology of magnetic fields, enabling unbiased surveys and imaging of dust-shrouded objects that are obscured at other wavelengths, enabling rapid response to and imaging of rapidly evolving transient sources, and tracking the formation and evolution of objects in the universe. The EVLA's primary technical elements include new or upgraded receivers for continuous frequency coverage from 1 to 50 GHz, new local oscillator, intermediate frequency, and wide bandwidth data transmission systems to carry signals with 16 GHz total bandwidth from each antenna, and a new digital correlator with the capability to process this bandwidth with an unprecedented number of frequency channels for an imaging array. The project also includes a new monitor and control system and new software that will provide telescope ease of use. The project was started in 2001 and is on schedule and within budget. Scientific observations with the new correlator started in March 2010. The structural modifications that convert the VLA antennas to the EVLA design were completed in May 2010. The project will be complete in December 2012 when the last receiver will be installed on an antenna.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.058 | 0.031 |
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".