Ukpik: testbed for a miniaturized robotic astronomical observatory on a high Arctic mountain
Bibliographic record
Abstract
Mountains along the northwestern coast of Ellesmere Island, Canada, possess the highest peaks nearest the Pole. This geography, combined with an atmospheric thermal inversion restricted to below ~1000 m during much of the long arctic night, provides excellent opportunities for uninterrupted cloud-free astronomy - provided the challenges of these incredibly remote locations can be overcome. We present a miniaturized robotic observatory for deployment on a High Arctic mountaintop. This system tested the operability of precise optical instruments during winter, and the logistics of installation and maintenance during summer. It is called Ukpik after the Inuktitut name for the snowy owl, and was deployed at two sites accessible only by helicopter, each north of 82 degrees latitude; one on rock at 1100 m elevation and another on a glacier at 1600 m. The instrument suite included at first an all-sky-viewing camera, with the later addition of a small telescope to monitor Polaris, both protected by a retractable weather-proof enclosure. Expanding this to include a narrow-field drift-scanning camera for studying extra-solar planet transits was also investigated, but not implemented. An unique restriction was that all had to be run on batteries recharged primarily by a wind turbine. Supplementary power came from a methanol fuel-cell electrical generator. Communications were via the Iridium satellite network. The system design, and lessons learned from three years of operation are discussed, along with prospects for time-domain astronomy from isolated, high-elevation polar mountaintops.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".