Pupil plane imager for estimation of turbulence over long horizontal paths
Bibliographic record
Abstract
A pupil plane imaging system, consisting of a camera and optics that image the entrance pupil of a telescope, measures scintillation induced by atmospheric turbulence. Algorithms are developed to estimate the distribution of turbulence from scintillation assuming the well known relationship between scintillation scale size and the range of turbulence layer. The algorithms were exercised using a 75 cm pupil within a 1 meter telescope located at North Oscura Peak in New Mexico, based on light from a source 52.6 km away. Estimates of the C(n)(2) profile over the path are derived using coarse range bins. From the C(n)(2) profile, an estimate of Fried's transverse coherence length was computed and compared with that from other sensors. The algorithm is tested in several ways. Error sources are discussed, including the intrinsic insensitivity of the technique to turbulence near the pupil.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".