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Record W2920952290 · doi:10.1504/ijsa.2018.10019853

Sustainable flight test project tools

2018· article· en· W2920952290 on OpenAlexaff
Darli Rodrigues Vieira, Paulo Quattrocchi

Bibliographic record

VenueInternational Journal of Sustainable Aviation · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsCertificationAviationKey (lock)Sample (material)Product (mathematics)Cost reductionNew product developmentFlight testManufacturing engineeringSystems engineeringEngineeringComputer scienceAeronauticsBusinessSimulationAerospace engineeringMarketingComputer securityEconomics

Abstract

fetched live from OpenAlex

One of the most important aspects of the development of a new aviation product is the testing and verification phase. This paper identifies procedures to optimise certification flight test campaigns as one troublesome and unpredictable aspect of aircraft development. Considering a large market historical sample from key aircraft manufacturers for the certification of their products, we conclude that a sustainable approach with flight hour reduction, selected engineering tools and management tools will result in a considerable reduction in fossil fuel expenses and overall product certification time and cost.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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