Oral History Interview with Frank Strebel, August 20, 2009
Bibliographic record
Abstract
The National Museum of the Pacific War presents an oral interview with Frank R. Strebel. Strebel was born in San Francisco 31 August 1919. He graduated from high school in 1938 and joined the Civilian Conservation Corps. Strebel joined the Army National Guard in 1937. His unit, Company F, 159th Infantry, 40th Infantry Division, was called to active duty in March 1941. The unit was sent to Camp San Luis Obispo for three months of training. Following maneuvers at Fort Lewis, the 159th was assigned to a coastal gun battery at Fort Cronkite, California. In May 1942, Strebel was assigned as a first sergeant in the 96th Infantry Division. From there, he attended Officer Candidate School and graduated with a commission. On 15 March 1944 he reported to Company F, 415th Infantry Regiment, 104th Division as a platoon leader. On 25 August 1944 the company arrived at Camp Kilmer, New Jersey and boarded the USS Lejeune (AP-74). They landed at Cherbourg, France 7 September 1944. On 15 October they boarded boxcars to Belgium where they joined the 1st Canadian Division in an assault. Strebel describes various combat situations in Aachen and Lammerdorf, Germany. His company suffered 60% casualties in their attempt to capture Lammerdorf, including the company commander. Strebel was wounded. Hospital stays in France and England followed. In January 1945 he returned to the United States and went to Hammond General Hospital until November 1945. He also had stays at the Camp Carson General Hospital in Colorado and the Bushnell General Hospital in Utah. He was discharged 19 May 1945.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.096 | 0.026 |
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".