3.4.2 Capability engineering for strategic decision making
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.
Bibliographic record
Abstract
Abstract The current paper summarizes the Capability Engineering Process (CEP) being developed to help decision making on strategic investments and divestments for the Canadian Forces and Department of National Defence. This effort is part of a technology demonstration effort called the Collaborative, Capability, Definition, Engineering and Management (CapDEM). The CEP introduces ways to increase strategic agility capability management in a world in constant evolution. A CEP application provides a set of options addressing a given capability gap. Among benefits, this process: (1) provides decision makers with timely strategic information through an iterative and incremental approach; (2) reduces time spent on unrealistic options by continuously pruning the solution space as early as possible; (3) provides operationally acceptable strategic options with direct involvement of the operational community into the solution development; and (4) provides feasible options by ensuring commitment and participation in developing solutions involving all of the organization's functional components: Personnel, R&D, Infrastructure, Concept development, Information management, and Equipment (known as PRICIE components in Canada).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it