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3.1.1 Transformative Affordability for System Architecture Design

2013· article· en· W2105440283 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

VenueINCOSE International Symposium · 2013
Typearticle
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsPaceArchitectureTransformative learningService (business)Focus (optics)Computer scienceSystems designProcess managementEngineeringSoftware engineeringBusinessMarketingSociologyGeography

Abstract

fetched live from OpenAlex

Abstract The US Department of Defense (DoD) has undergone major evolutionary shifts in recent years that include movement from a platform focus to a mission objective, from single‐purpose solutions to systems with adaptive relevancy, from focus on primary systems only to embracing holistic solutions integrating enabling and support systems and from acquisition‐only costs to complete life cycle cost analyses. Dr. Robert Gates, challenged contractors to define and deliver compliant ‘80% solutions‘.* How does this affordability challenge change architecture design? * Dr. Gates: “Finally, I concluded we needed to shift away from the 99 percent exquisite, service‐centric platforms that are so costly and so complex that they take forever to build and only then are deployed in very limited quantities. With the pace of technological and geopolitical change and the range of possible contingencies, we must look more to the 80 percent multi‐service solutions that can be produced on time, on budget and in significant numbers.”

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: Methods · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.526

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 head0.021
GPT teacher head0.239
Teacher spread0.219 · 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