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Record W2755658620 · doi:10.2514/6.2017-5145

Innovative Test Operations to Support Orion and Future Human Rated Missions

2017· article· en· W2755658620 on OpenAlexaff
Rafael Garcia, William Koenig, Richard F. Harris, Michael See, Jill Dobson, Scott D. Norris

Bibliographic record

VenueAIAA SPACE and Astronautics Forum and Exposition · 2017
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsTest (biology)Computer scienceAeronauticsEngineeringSystems engineeringGeology

Abstract

fetched live from OpenAlex

This paper describes how the Orion program is implementing new and innovative test approaches and strategies in an evolving development environment. The early flight test spacecraft are evolving in design maturity and complexity requiring significant changes in the ground test operations for each mission. The testing approach for EM-2 is planned to validate innovative Orion production acceptance testing methods to support human exploration missions in the future. Manufacturing and testing at Kennedy Space Center in the Neil Armstrong Operations and Checkout facility will provide a seamless transition directly to the launch site avoiding transportation and checkout of the spacecraft from other locations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.009
GPT teacher head0.246
Teacher spread0.237 · 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 designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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