Validation and Verification of NATO Network Enabled Capabilities (Validation et verification des capacites reseau de l'OTAN (NNEC))
Bibliographic record
Abstract
The purpose of this Workshop (WS) was to bring together members from participating NATO countries to discuss the Verification and Validation (V&V) of a NATO Network Enabled Capability. V&V must be built into the development of network enabled capabilities in an iterative approach starting with the initial concept of operations. Furthermore, as an NNEC collects, processes, integrates and disseminates information, the V&V of an NNEC in essence feeds the research and development of that NNEC. The workshop was convened at Edwards AFB, California, USA on 11-14 Sep 2007. Workshop participating countries included Canada, Estonia, Italy, Netherlands, Spain, Turkey, UK, and USA. The workshop discussed formulated a top level roadmap that included a working definition of NNEC for V&V, definition and prioritization of V&V capabilities, shortfalls, key players, initiatives, and future guidelines. It was agreed to initiate within Working Session C of the SCI panel the activities to address all of the above identified items. This effort should start with an immediate follow-on Task Group to work the details of a V&V of NNEC roadmap. A TAP/TOR for initial task group should be submitted in Oct 2007 for start in April 2008.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.060 | 0.086 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".