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Record W4321615296 · doi:10.56094/jss.v58i1.216

Difficulties with Replacing Crew Launch Abort Systems with Designed Reliability

2023· article· en· W4321615296 on OpenAlex

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.

Bibliographic record

VenueJournal of System Safety · 2023
Typearticle
Languageen
FieldEngineering
TopicSpace Exploration and Technology
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsAbortCrewHuman spaceflightAeronauticsProcurementReliability (semiconductor)AviationEngineeringSAFERComputer scienceSpacecraftSystems engineeringComputer securityBusinessAerospace engineering

Abstract

fetched live from OpenAlex

As the space industry continues to innovate and new paradigms arise to challenge the status quo, human spaceflight is now perceived as safer and more accessible than ever before. This has led to a new line of thinking in which crewed launch vehicles should be reusable and reliable like commercial airplanes, forgoing the need for an abort system. This paper will counter that line of thought with an analysis of the spectrum of coverage historical crew abort systems provided during launch and use historical data from launch rate successes and failures to glean insight into what reliability in the human spaceflight industry can expect when designing the vehicles of the future. This historical launch vehicle reliability will then be compared to system safety standards used in the commercial aviation industry to understand if future designs truly need a crew abort system. Through this analysis, the rationale for why these crew abort systems have historically been used can be better understood.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.188
Teacher spread0.180 · 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