Exploring the Mysteries of the Cosmos on the MOST Microsatellite Mission
Bibliographic record
Abstract
The MOST (Microvariability and Oscillations of STars) astronomy mission under the Canadian Space Agency.s Small Payloads Program is Canada.s first space science microsatellite and is scheduled to launch in June 2003. The MOST science team will use the satellite to conduct long-duration stellar photometry observations in space. The primary science objectives include: measuring light intensity oscillations in solar type stars; determining the age of nearby .metal-poor sub-dwarf. stars, which will in turn allow a lower limit to be set on the age of the Universe; and detecting the first reflected light from orbiting exoplanets and using it to determine the composition of their atmospheres. To make these measurements, MOST incorporates into a microsatellite design a small (15 cm aperture), high-photometric-precision optical telescope and a high performance attitude control system that is revolutionary in its pointing accuracy for a microsatellite. A key hurdle that the MOST mission had to overcome was that of access to space. MOST as initially conceived was designed to launch as a secondary payload aboard a Delta II rocket carrying Canada.s Radarsat-2 mission. However, subsequent delays in the Radarsat-2 program have pushed its launch to the end of 2004 or beyond. Access to space was extremely important to the MOST mission because of the revolutionary science that is being done. Consequently, the Canadian Space Agency contracted with Eurockot to provide launch services using a .Rockot. launch vehicle launching from Plesetsk, Russia. As we prepare for the launch in June 2003, the paper will present a summary of the science goals of the mission, will highlight the progress of the integration team in preparing the satellite for launch, and will reflect on the impact that changing launch vehicles has had on the satellite in our quest for access to space.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".