<title>Steady-state analysis of the multi-tethered aerostat platform for the Large Adaptive Reflector telescope</title>
Bibliographic record
Abstract
The Large Adaptive Reflector (LAR), currently being developed at the National Research Council Canada, is a low-cost, large- aperture, wide-band, cm-wave radio telescope designed for implementation in the Square Kilometer Array (SKA). The LAR consists of a 200 m diameter, actuated-surface, parabolic reflector with a feed located at a 500 m focal length. Since the feed must be positioned on a 500 m hemisphere centered about the reflector and between a zenith angle of 0 degree(s) to 60 degree(s), an innovative method for feed positioning is required. This feed positioning will be achieved using a high- tension structure consisting of a 4100 m3 helium aerostat supporting an array of tethers. The length of each tether can be controlled through the use of winches, resulting in accurate control of the feed position. The feasibility of the tethered aerostat feed-positioning system is of critical importance to the success of the LAR. Extensive steady-state analyses of the multi-tethered aerostat have been completed and provide strong evidence that this feed-positioning system will operate reliably in moderate weather conditions (10 m/s constant wind velocity with 2.5 m/s wind gusts). The framework of these analyses and the corresponding results will be presented.
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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 | 0.000 | 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) | 0.002 | 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".