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Record W2749032356 · doi:10.4271/2017-01-2085

Combination of Experimental and Computational Approaches to A320 Wing Assembly

2017· article· en· W2749032356 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2017
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsnot available
FundersAlzheimer Society Research ProgramSaint Petersburg State University
KeywordsWingComputer scienceAerospace engineeringAeronauticsEngineering

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">The paper is devoted to the simulation of A320 wing assembly on the base of numerical experiments carried out with the help of ASRP software. The main goal is to find fasteners’ configuration with minimal number of fastening elements that provides closing of admissible initial gaps.</div><div class="htmlview paragraph">However, for considered junction type initial gap field is not known a priori though it should be provided as input data for computations. In order to resolve this problem the methodology of random initial gap generation based on available results of gap measurements is developed along with algorithms for optimization of fasteners' configuration on generated initial gaps.</div><div class="htmlview paragraph">Presented paper illustrates how this methodology allows optimizing assembly process for A320 wing.</div></div>

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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