MétaCan
Menu
Back to cohort
Record W3100176039 · doi:10.1089/ast.2019.2031

The AMADEE-18 Mars Analog Expedition in the Dhofar Region of Oman

2020· article· en· W3100176039 on OpenAlexaff
Gernot Groemer, Sophie Gruber, Stefan Uebermasser, Alexander Soucek, E.A. Lalla, João Lousada, Sebastian Sams, Nina Sejkora, Stefanie Garnitschnig, Birgit Sattler, Pamela Such

Bibliographic record

VenueAstrobiology · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsYork University
Fundersnot available
KeywordsMars Exploration ProgramExploration of MarsContext (archaeology)WorkflowCrewAstrobiologySpace explorationResearch centerEarth scienceAeronauticsEngineeringGeologyComputer scienceGeographyAerospace engineeringArchaeologyPolitical sciencePhysics

Abstract

fetched live from OpenAlex

From February 1 to 28, 2018, the Austrian Space Forum, in cooperation with the Oman Astronomical Society and research teams from 25 nations, conducted the AMADEE-18 mission, a human-robotic Mars expedition simulation in the Dhofar region in the Sultanate of Oman. A carefully selected field crew, supported by a Mission Support Center in Innsbruck, Austria, conducted 19 experiments relevant to astrobiology, engineering disciplines, geoscience, operations research, and human factors. This expedition was the 12th in a series of analog missions that emulate selected aspects of the science expected for a human Mars mission, including the characterization of the (paleo)geological environment, human factors studies, and the search for biomarkers. In particular, an Exploration Cascade was deployed as a suggested workflow for coordinating the timing and location of the respective instruments and experiments. In validation of this workflow, the decision-making interaction between the field and the Mission Support Center was studied. This article introduces the AMADEE-18 mission and provides the mission-specific context for the other contributions of this special issue.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.112

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 head0.030
GPT teacher head0.229
Teacher spread0.199 · 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 designObservational
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

Citations19
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAstrobiologySame topicPlanetary Science and ExplorationFrench-language works237,207