Canada-France-Hawaii Telescope image quality improvement initiative: thermal assay of the observing environment
Bibliographic record
Abstract
As part of the image quality (IQ) assessment and improvement initiative being carried out at the 3.6m Canada France Hawaii Telescope (CFHT) on Mauna Kea, Hawaii, our objective in the work reported here is to obtain a systematic assay of thermal sources within the dome and in the summit environment around the observatory, and therefore mitigate their contributions to convective instability leading to 'dome seeing'. Toward this, we undertook a nighttime overflight to capture thermal images with a calibrated infrared camera of the outer structures of CFHT and the neighboring observatories on the summit ridge, as well as of a significant area of the surrounding terrain. The same thermal camera was then used to image heat sources within the dome. Using a convective heat transfer model, all these measured surface temperatures were converted to heat fluxes, and thus used to build a thermal assay of the dome. In addition, using button type temperature loggers, we simultaneously recorded the nighttime dome skin temperatures of CFHT and two other observatories over a weeklong period to evaluate nighttime supercooling of the dome skin due to radiation to the cold night sky. As a complementary goal we compared the efficacy of different paints and coatings used in observatories to minimize this effect. Though similar studies have been carried out at other observatories, the results are rarely available in published literature. Therefore, here we explain our methodologies, along with a detailed discussion of our results and inferences to serve as a useful resource to the larger observing community.
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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 | 0.001 | 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 | 0.001 | 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".