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5.1.5 A Systems Engineering Methodology for Combat Systems Development

2002· article· en· W2013772992 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueINCOSE International Symposium · 2002
Typearticle
Languageen
FieldEngineering
TopicTechnology Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsSystem of systemsSystems development life cycleLitanyEngineeringEngineering managementRisk analysis (engineering)Computer scienceSystems engineeringSoftware developmentOperations researchProcess managementBusinessSystems designSoftwareSoftware development processGeography

Abstract

fetched live from OpenAlex

Abstract Combat system development is difficult to do well; many issues surround the development of such systems. The history of the creation of large, complex, socio‐technical systems has been marred by a litany of project failures. Poor project outcomes result in business failure and significantly reduce the capability that can be achieved for the modest defense budgets of countries like Australia, Austria, Belgium, Canada, the Netherlands, Spain and Sweden. This situation is being exacerbated by the increasing dependence of modern military systems on software and the increasing complexity of such systems. This paper highlights major issues faced by the defense industries of ‘intermediate’ nations such as those listed. It proposes a solution in the form of a systems engineering methodology appropriate to combat system development.

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 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: none
Teacher disagreement score0.894
Threshold uncertainty score0.735

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 communication0.0000.000
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 head0.039
GPT teacher head0.249
Teacher spread0.210 · 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