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Record W7097220612

The MOST Microsatellite Mission: Canada’s First Space Telescope

2008· article· en· W7097220612 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsnot available
Fundersnot available
KeywordsTelescopeSpitzer Space TelescopePhotometry (optics)Hubble space telescopeBoomSatelliteSpace Science
DOInot available

Abstract

fetched live from OpenAlex

Abstract. The MOST (Microvariability and Oscillations of STars) astronomy mission has been chosen by the Canadian Space Agency’s Small Payloads Program to be Canada’s first space science microsatellite, and is currently planned for launch in late 2001. The MOST science team will use the MOST satellite to conduct long-duration stellar photometry observations in space. A major science goal is to set a lower limit on the age of several nearby “metal-poor sub-dwarf” stars, which may in turn allow a lower limit to be set on the age of the Universe. To make these measurements, MOST will incorporate a small (15 cm aperture), high-photometric-precision optical telescope to be developed by UBC. The MOST bus and ground stations are being developed by Dynacon and the University of Toronto, in collaboration with AMSAT Canada. Several of the bus subsystems are based on similar designs that have been flown on past AMSAT microsatellites. However, the MOST attitude control system is unusual for a microsatellite, requiring highlyaccurate (< 30 arc-seconds) three-axis inertially-fixed stabilization, far better than can be achieved using the gravitygradient boom stabilization approach typical of many past microsatellites. Dynacon will provide the MOST ACS, based on its Miniature Reaction Wheel (MRW) and High Performance Attitude Control (HPAC) products. MOST’s HPAC capability will enable it to be one of the first operational space science microsatellites.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.168
Teacher spread0.162 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2008
Admission routes1
Has abstractyes

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