ADAPTIVE OPTICS FOR ASTRONOMY: A STRONG CANADIAN ASSET
Bibliographic record
Abstract
Thanks to a rich legacy of more than 20 years, Canada is established as a strong leader in the eld of adaptive optics. Adaptive optics is absolutely critical for current and future ground based telescopes, and the key to maintaining Canada’s leadership in the coming decade and beyond will be a strong synergy between HIA, Canadian universities and Canadian industry. 1. PAST ACCOMPLISHMENTS AND CURRENT STATUS 1.1. AO instrumentation for current telescopes Canada’s leadership in AO started well before the beginning of the last decade, with the delivery to CFHT of HRCAM, a \simple tip-tilt corrector in 1988 that produced the highest-resolution images before HST, and PUEO (in collaboration with France, in 1995) { the most user-friendly and scientically productive AO system of its generation. That early investment in AO paid great dividends with the successful delivery of HIA-made Altair to Gemini North in 2002. Altair, which initially worked in natural guide star (NGS) mode, achieved an unprecedented level of automation (\one button operation) and of integration with the telescope, leading to a scientic productive instrument, very competitive with similar instruments being deployed at 8-meter class telescopes in the same time frame. In 2005, Gemini North was equipped with a laser guide star (LGS). This vastly increased Altair’s sky coverage, and, especially with the coupling in 2006 with the integral eld spectrograph NIFS (a desirable combination also favored at VLT and Keck), dramatically increased the scientic reach of AO,
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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 teacher head, 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".