Bibliographic record
Abstract
Strehl ratios achieved on bright guide stars by 19 adaptive optics (AO) systems of various dimensions are examined. Both types of systems exhibit a similarly stronger attenuation of instrumental aberrations with smaller subapertures. With the same number of wave‐front sensor subapertures, curvature systems are generally found to be more efficient than Shack‐Hartmann systems at attenuating turbulence‐induced optical phase variance. Consequently, curvature systems use fainter guide stars to achieve the same performance as Shack‐Hartmann systems. The contrast is stronger for larger systems. Possible causes of these differences are discussed. Calibration errors of non–common‐path aberrations appear to be the most important. The compensation of the guide star image itself seems to be beneficial for large curvature systems. The likely performance of future very large systems are briefly discussed. A plea is made to encourage astronomical AO teams to uniformly and optimally characterize the on‐sky performance of their systems.
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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) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".