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Record W2014487321 · doi:10.1109/aero.2005.1559585

Design for Flexible and Scalable Avionics Systems

2005· article· en· W2014487321 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicReal-Time Systems Scheduling
Canadian institutionsYork University
Fundersnot available
KeywordsComputer scienceScalabilityFlexibility (engineering)AvionicsTask (project management)Set (abstract data type)Distributed computingScale (ratio)Work (physics)Product (mathematics)Risk analysis (engineering)Systems engineeringSoftware engineeringEngineeringDatabase

Abstract

fetched live from OpenAlex

Large-scale complex embedded systems pose unique problems to developers. The development of these systems is often performed in a concurrent and iterative fashion. This has lead to a great deal of work on developing processes and product technologies to support scalability and flexibility, i.e. managing change. One example of this is the DARPA funded MoBIES project which approaches the problem by allowing the designer to concentrate on the model level. From a real-time systems perspective, one area that needs greater attention is that of task allocation and attribute assignment. The reason is that, whilst a great deal of work has been done on task allocation, it has been targeted at meeting the current set of timing requirements without giving appropriate consideration for the need to manage change

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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.788
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.038
GPT teacher head0.265
Teacher spread0.226 · 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

Quick stats

Citations2
Published2005
Admission routes1
Has abstractyes

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