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11.4.3 Advancing the Canadian Capability Engineering Approach

2006· article· en· W2064941075 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueINCOSE International Symposium · 2006
Typearticle
Languageen
FieldEngineering
TopicSystems Engineering Methodologies and Applications
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsProcess (computing)Systems engineeringEngineering managementEngineeringEngineering design processComputer scienceOrder (exchange)Concurrent engineeringProcess managementManagement scienceOperations managementMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The Collaborative Capability Definition Engineering and Management Technology Demonstration (CapDEM TD) project is investigating Capability Engineering (CE) in order to support the Capability‐Based Planning (CBP) decision‐making process. This paper presents the evaluation effort being applied to the Capability Engineering approach, a methodology based on the systems engineering paradigm and articulated around three axes: People, Process and Materiel. Originating from the laboratories of Defence R&D Canada, the CapDEM effort is now evolving from theory into practice, based on an on‐going evaluation strategy concretely realized via three validation exercises that consist of realistic simulations of people applying the process and materiel to resolve capability gaps. This paper details the evaluation strategy and includes lessons learned from the first and second validation exercises. The tenets and expectations from the final exercises will form the final part of the paper, with the intent of providing insight into the advancement of capability engineering.

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: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.983

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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