Inuksuit: robotic astronomical site-testing stations in the Canadian High Arctic.
Bibliographic record
Abstract
Coastal mountains at Canada's northern tip possess many of the desirable properties that make the Antarctic glacial plateau attractive for astronomy: they are cold, high, dry, and in continuous darkness for several months in winter. Satellite images suggest that they should also benefit from clear skies for a fraction of time comparable to the best mid-latitude sites, and conventional site-selection criteria point to good seeing. In order to confirm these conditions, we are testing three mountain sites on northwestern Ellesmere Island, in Nunavut. On each we have installed a compact, autonomous site-testing station consisting of a meteorological station, a simple optical/near-infrared camera for sensing cloud cover, and - at one site - a more advanced all-sky viewing camera. The systems were deployed by helicopter and run on batteries recharged by wind (a compact methanol fuel cell is under study as a supplementary power source). Effective two-way communications via the Iridium satellite network allows a limited number of highly compressed images to be transferred. The full-winter dataset is stored at the site on flash-drives, thus requiring a return visit to retrieve, but day-to-day station performance can be assessed using telemetry and a computer model. Based on site-testing results, the plan is to select one site for the addition of a seeing monitor and a small but scientifically productive telescope. Copyright 2008 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".