An access to innovation program to enhance the technological capabilities of the armed forces
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
As part of “Strong, Secure, Engaged: Canada’s Defence Policy” (Department of National Defence (2017) Strong, Secure, Engaged) released in 2017, the Canadian Department of National Defence (DND) announced the creation and implementation of an access to innovation program to be called the “Innovation for Defence Excellence and Security (IDEaS)” Program. The IDEaS Program was introduced to support, increase, and sustain science and technology (S&T) community capacity external to DND that can generate new ideas and formulate solutions to Canada’s current and future defence and security innovation challenges. This paper will explore the design of this new business model through the delivery of the first proof of concept to have gone through the whole IDEaS cycle, in order to showcase the validity of this concept and processes. It also demonstrates that IDEaS has allowed a closer relationship with innovators and firms that had never worked with the defence industry, as well as the identification of novel solutions to a host ofproblems/challenges facing defence and security.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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