6.4.2 A Metric Framework for Capability Definition, Engineering and Management
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 As defence planning and management evolves from a platform‐centric, threat‐based approach toward a capability‐based paradigm, the need for a rigorous approach to systems engineering at the capability level is amplified. This is because capability‐based plans incorporate system‐of‐systems configurations with varying developmental timeframes that must deliver interoperable effects on the battlefield. In addressing this challenge, a capability‐based planning construct is being examined within the Department of National Defence. This construct is supported by integrating and enabling concepts like enterprise architectures, system‐of‐systems engineering principles and capability metrics. While an architecture framework is useful for developing functional requirements of a capability, a metric framework, as this paper contends, can be used as a guide for defining and articulating desired quality characteristics. This paper describes the concept of a capability metric framework, and how it has been applied to define capability goals and evaluate implementation options.
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