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Record W2228091159

NASA's Lunar Polar Ice Prospector, RESOLVE: Mission Rehearsal in Apollo Valley

2012· article· en· W2228091159 on OpenAlex
W. E. Larson, Martin Picard, Jacqueline Quinn, Gerald B. Sanders, A. Colaprete, R. C. Elphic

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Astronautical Congress · 2012
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsCanadian Space Agency
Fundersnot available
KeywordsPayload (computing)Impact craterOrbiterAstrobiologyApolloTimelineWater iceIcy moonFar side of the MoonSpace explorationRemote sensingAeronauticsNASA Deep Space NetworkGeologySpacecraftAerospace engineeringPlanetEngineeringComputer scienceGeographySaturnGeophysicsPhysicsAstronomyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

After the completion of the Apollo Program, space agencies didn't visit the moon for many years. But then in the 90's, the Clementine and Lunar Prospector missions returned and showed evidence of water ice at the poles. Then in 2009 the Lunar Crater Observation and Sensing Satellite indisputably showed that the Cabeus crater contained water ice and other useful volatiles. Furthermore, instruments aboard the Lunar Reconnaissance Orbiter (LRO) show evidence that the water ice may also be present in areas that receive several days of continuous sunlight each month. However, before we can factor this resource into our mission designs, we must understand the distribution and quantity of ice or other volatiles at the poles and whether it can be reasonably harvested for use as propellant or mission consumables. NASA, in partnership with the Canadian Space Agency (CSA), has been developing a payload to answer these questions. The payload is named RESOLVE. RESOLVE is on a development path that will deliver a tested flight design by the end of 2014. The team has developed a Design Reference Mission using LRO data that has RESOLVE landing near Cabeus Crater in May of2016. One of the toughest obstacles for RESOLVE's solar powered mission is its tight timeline. RESOLVE must be able to complete its objectives in the 5-7 days of available sunlight. The RESOLVE team must be able to work around obstacles to the mission timeline in real time. They can't afford to take a day off to replan as other planetary missions have done. To insure that this mission can be executed as planned, a prototype version of RESOLVE was developed this year and tested at a lunar analog site on Hawaii, known as Apollo Valley, which was once used to train the Apollo astronauts. The RESOLVE team planned the mission with the same type of orbital imagery that would be available from LRO. The simulation team prepositioned a Lander in Apollo Valley with RESOLVE on top mounted on its CSA rover. Then the mission simulation began as the operations team's consoles came alive with data and images. They executed the mission just like the real mission with lunar communications delays and limited bandwidth and a realistic remote mission control room. This paper will describe the RESOLVE payload in detail and describe the results of the mission simulation in Hawaii.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.693

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 head0.012
GPT teacher head0.254
Teacher spread0.243 · 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