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A Research Agenda for Systems of Systems Architecting

2007· article· en· W2073163098 on OpenAlexaff
Elliot Axelband, Thomas Baehren, Dave Dorenbos, Azad M. Madni, Paul Robitaille, Ricardo Valerdi, Barry Boehm, Scott Jackson, Gerald Nadler, Stan Settles

Bibliographic record

VenueINCOSE International Symposium · 2007
Typearticle
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsLockheed Martin (Canada)
FundersFederal Emergency Management Agency
KeywordsBrainstormingContext (archaeology)PrioritizationField (mathematics)Engineering managementEngineering ethicsPolitical scienceProcess managementComputer scienceEngineering

Abstract

fetched live from OpenAlex

Abstract This paper documents the activity of a workshop on defining a research agenda for Systems of Systems (SoS) Architecting, which was held at USC in October 2006. After two days of invited talks on critical success factors for SoS engineering, the authors of this paper convened for one day to brainstorm topics for the purpose of shaping the near‐term research agenda of the newly convened USC Center for Systems & Software Engineering. The output from the workshop is a list of ten high‐impact items with corresponding research challenges in the context of SoS Architecting. Each item includes a description of the research challenges, its link to contemporary academic or industrial problems, and reasons for advocacy of that area. The items were assessed in terms of value and difficulty to determine a prioritization both for the CSSE's future research agenda and for others in the field.

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)0.079
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.420

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0790.041
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0070.004
Science and technology studies0.0100.019
Scholarly communication0.0310.038
Open science0.0040.014
Research integrity0.0150.018
Insufficient payload (model declined to judge)0.0150.003

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 head0.099
GPT teacher head0.378
Teacher spread0.279 · 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 designTheoretical or conceptual
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

Citations14
Published2007
Admission routes1
Has abstractyes

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