LINC-NIRVANA: MCAO toward Extremely Large Telescopes
Bibliographic record
Abstract
LINC-NIRVANA is a Fizeau (imaging) interferometer exploiting the full spatial resolution of a 23 m class telescope in the combined beam of the Large Binocular Telescope supported through Multi-Conjugated Adaptive Optics (MCAO). By means of science cases, we show how LINC-NIRVANA takes advantage of the MCAO, increasing the sky coverage of the instrument and the field of view for the Fringe and Flexure tracker. We introduce the MCAO system of LINC-NIRVANA in detail, which in a first step will be installed with two deformable mirrors per arm and has the provision to be upgraded with a third mirror. The MCAO system implements several novel concepts proposed for extremely large telescopes, such as layer oriented MCAO, optical co-adding of guide stars, or Multiple Field of View sensing. LINC-NIRVANA will demonstrate some of the concepts for the first time on sky.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".