HEART: Gemini North Adaptive Optics (GNAO) real-time controller using the Herzberg Extensible Adaptive Real-time Toolkit (HEART)
Bibliographic record
Abstract
In July of 2020 the Herzberg Astronomy and Astrophysics Research Centre was contracted to provide the Gemini Telescopes Observatory with a facility class Adaptive Optics (AO) Real Time Controller (RTC) suitable to run existing and future Adaptive Optics Systems. This Gemini Adaptive Optics Real-Time Controller (GAO RTC) is using the Herzberg Extensible Adaptive Real-time Toolkit (HEART), a C/Python software framework for constructing RTCs that targets general-purpose CPUs and standard networking hardware. Initially a fully simulated stand-alone RTC will be completed which will be suitable for experimentation in association with end-to-end AO simulation software. Subsequently, it will be reconfigured and extended to support hardware interfaces to the future Gemini North Adaptive Optics (GNAO) facility. This paper will provide an overview of the customization of the HEART design for GNAO, current state of the development, how this system state changes during operation, and how HEART was de-risked.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.008 |
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".