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Record W3000486568 · doi:10.1061/9780784481899.111

An Introduction to Assembly Integration and Test (AIT) Requirements for Martian Systems

2018· article· en· W3000486568 on OpenAlexaffabout
Alexander M. Jablonski, Daniel Showalter, Jay Weng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMartianMars Exploration ProgramMartian surfaceAstrobiologyExploration of MarsRegolithMartian soilAtmosphere of MarsEnvironmental scienceMars landingAerospace engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper has two main objectives: to review the current status of the Martian environmental conditions that impact Martian systems, and to derive from them the top-level requirements for the assembly, integration, and test (AIT) of Martian systems. Each planetary system must be space qualified in order to survive harsh planetary conditions on top of other mission phases like launch, cruise from Earth to the specific celestial body, entry, descent and landing (EDL), and end of operation. In general, Martian systems include three types of landers: long term permanent stations, rovers, and any other landers for long term operation required for unmanned or manned missions. The Martian environmental conditions from the engineering points of view include: temperature variation, radiation environment, Martian gravity, regolith/soil conditions (dust), and Martian geological features, depending on the Martian surface mission profile and their impact on any system operating on Mars for the required time range. Then, top-level AIT requirements for surface Martian systems are developed and presented based on knowledge of Martian environmental conditions. The impact of the most recent Martian landers and orbiters is explained. Future Martian missions are also briefly described. Special attention is given to AIT requirements associated with the thermal variation, radiation environment, Martian atmosphere, and dust. Finally, conclusions and recommendations from a Canadian perspective are also included.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0200.014

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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
Published2018
Admission routes2
Has abstractyes

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Same topicPlanetary Science and ExplorationFrench-language works237,207