Bibliographic record
Abstract
The Canadian War Museum supports developmental research. This article is a by-product of the author’s continuing research into Canadian casualty records of the Korean War. This research helps to create a better picture of the makeup of the Canadian Army Special Force in Korea. When completed, it will shed greater light on when, where, and under what circumstances the 516 Canadians who are listed in the Korean War Book of Remembrance died. The research consists of a full review of the service records of Canadian military personnel who died in Korea or in support of the war from 1950 to 1956. The atip division of the Library and Archives Canada has generously supported this research through conducting speedy review and release of the necessary files. The author would like to thank Lesley Bilton-Bravo, Mike Abbots, Marc Frêve, and Le Phung for their work in providing access to the records and for screening the files for sensitive personal information.\nLe Musée canadien de la guerre soutient les recherches en matière de développement. Découlant des recherches assidues de l’auteur sur les archives canadiennes des victimes de la Guerre de Corée, cet article précise la nature de la force spéciale canadienne en Corée. À terme, il jettera un éclairage nouveau sur les 516 Canadiens figurant au livre du souvenir de la Guerre de Corée, précisant le moment, l’endroit et les circonstances de leur décès. Cette recherche consiste en un examen complet des dossiers du personnel militaire canadien mort en Corée ou en service pour cette guerre, entre 1950 et 1956. La division aiprp de Bibliothèque et Archives Canada a généreusement soutenu cette recherche en étudiant et partageant rapidement les dossiers nécessaires. L’auteur aimerait remercier Lesley Bilton-Bravo, Mike Abbotts, Marc Frêve, et Le Phung de lui avoir donné accès aux dossiers, tout en protégeant les informations personnelles de nature confidentielle.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".