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Record W2724232086 · doi:10.4050/f-0071-2015-10279

525 Aircraft Zero, The Relentless Advanced Systems Integration Lab

2015· article· en· W2724232086 on OpenAlexaff
Stephanie Hoelscher

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsBell Helicopter Textron (Canada)
Fundersnot available
KeywordsAeronauticsZero (linguistics)Aerospace engineeringComputer scienceSystems engineeringEngineering

Abstract

fetched live from OpenAlex

Development of the first fly-by-wire (FBW) commercial helicopter requires an integrated approach to design, testing, validation, and verification. The Bell 525 Relentless Advanced Systems Integration Lab (RASIL) - or "Aircraft Zero" - provides a platform for Vehicle Management System (VMS) hardware integration and associated validation and verification testing, including certification testing. The utility of the 525 RASIL is the ability to perform system testing ahead of and in support of the 525 flight test, envelope expansion, and certification program. RASIL testing is supporting the development of the 525 FBW control laws through initial design, open loop, closed loop, failure and certification related testing. The RASIL has seen advances in efficiency through automated testing and results verification, scripted failure insertion, and streamlined lab reconfiguration. Leveraging RASIL functionality and the wide array of testing conducted there, the 525 program achieves increased safety and a reduction in "real" aircraft flight testing that can be realized with commensurate cost and schedule savings.

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)0.002
metaresearch head score (Gemma)0.001
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0480.015

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 head0.058
GPT teacher head0.270
Teacher spread0.212 · 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
GenreOther

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

Citations1
Published2015
Admission routes1
Has abstractyes

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