Oral History Interview with Ken Miller, February 18, 2005
Bibliographic record
Abstract
The National Museum of the Pacific War presents an oral interview with Colonel Ken Miller. Miller was born in Toronto, Canada and raised in California. As a student, he became interested in radio communications and went into the California National Guard in 1939. In the Guard he was wth 102nd Signal Radio Intelligence Company. Miller was on his way to Hawaii and then the Philippines when the Japanese attacked. The ship he was on returned to San Francisco and he was sent to Officer Candidte School. Upon graduating, he was assigned to the 8th Army Air Force Radio Squadron Mobile at Camp Pinedale where he trained units headed for the field overseas. Eventually, he shipped out with the last unit he trained and was stationed at Guam prior to the invasion of Iwo Jima. Once the island was secure, Miller went in and established his radio station where he intercepted Japanese radio traffic. Miller continues with several anecdotes about being on Iwo Jima: recovering Japanese code books from aircraft crashes; surfing; being attacked by Japanese planes; witnessing airplane ditches and crashes; receiving mail; being attacked at night by Japanese holdouts; working with Japanese Americans on Iwo Jima; a typhoon; etc. When the war ended, Miller was relieved and retuned to the US where he left the service only to join again and make a career out of it.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.103 | 0.018 |
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".