Oral History Interview with John Goodenough, July 29, 2016
Bibliographic record
Abstract
The National Museum of the Pacific War presents an oral interview with John Goodenough. Goodenough was born in Jena, Germany in 1922 to American parents. After being educated in private schools, he attended Yale University receiving his degree in 1944. He entered the United States Army Air Forces in 1943. He was commissioned, after being trained as a meteorologist and was sent to Newfoundland. He worked on weather predictions prior to the Normandy landing. He later served in the Azores. Following his discharge in 1948 he attended the University of Chicago, utilizing the GI Bill to attain a Ph.D. in physics. He recalls his tutelage under noted physicist Clarence Zener. Goodenough discusses his involvement in the development of the lithium-ion battery utilized in the development of the personal computer. He concludes the discussion, telling of his career at the University of Texas and his ultimate retirement. Goodenough was awarded the Novel Prize for Chemistry in 2019.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.138 | 0.032 |
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".