10.3.2 Functional Capabilities In Complex Project Engineering
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 Recent performance in the acquisition of large scale defense systems has not met expectations. The acquisition community in the U.S. Department of Defense has been challenged by the department's transition to network‐centric warfare, which leverages complex system collaborations to achieve significant new capabilities. Developing systems of systems or systems of services requires evolved system engineering and project management practices, and better integration of both. This paper presents early learning in this regard from one ongoing system‐of‐systems development program, the Single Integrated Air Picture (SIAP). A “functional capability” concept evolved to become a potentially unique definition of a project that has proved useful in a system‐of‐systems development context. This paper then explains a recommended structured‐development approach built on Functional Capabilities that yields artifacts promoting communication, specification, and work phasing. It also compares the approach to the CMMI™ to demonstrate the wide process applicability of Functional Capabilities.
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