Canada's Navy and the National Research Council
Bibliographic record
Abstract
For much of its 100-year history the Canadian Navy has been a partner of the National Research Council in naval technology development. The relationship began in 1933 and progressed to the point where, in 1940, NRC became the official scientific establishment of the Navy, responsible for all research development and scientific liaison. During the post-war period, NRC collaborated with the new Naval Research Establishment on the development of new naval technologies, including HMCS Bras D’or and the Variable Depth Sonar towbody, a technology still in use today. NRC contributed its expertise to all new vessel classes throughout the latter half of the 20th century. With the new millennium it has collaborated on projects as diverse as roll damping for the Maritime Coastal Defence Vessels, to better fuel efficiency for the Canadian Patrol Frigates. Those contributions have resulted in very practical benefits to naval operations, including improved safety and lower operational costs.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.133 | 0.044 |
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".