Recent Additions to the Canadian War Museumâs Vehicle Collection
Bibliographic record
Abstract
A s a national institution the Canadian War Museum strives to bring before its audience the contributions of the military to national life.This is always impossible to accomplish in its fullest sense.and is perhaps especially so in the case of the CWM's vehicle collection.It is, of course, impossible to attempt to collect examples of every vehicle used or produced in Canada.With the passing of time examples in good condition of Canada's contributions to mechanized war are becoming very scarce.During the past year, however, the museum has made significant advances in adding to its collection of Canadian-made Second World War vehicles.During this conflict, Canada was asked to provide vast quantities of arms, munitions, vehicles.and other equipment to support the Allied war effort.This huge national effort reached a peak with the production of more than 850,000 military vehicles.1 Canadian vehicles, both of military and commercial patterns, were sent as far away as South Africa and Burma, where they earned a reputation for solid service.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.019 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.143 | 0.030 |
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".