Bibliographic record
Abstract
This book pieces together the largely forgotten story of the bomber, Getaway Gertie, and an eclectic group of enthusiasts who have spent years searching for it. At the height of World War II, a B-24 Liberator bomber vanished with its crew while on a training mission over upstate New York. The final hours and ultimate resting place of pilot Keith Ponder and seven other US aviators aboard the plane remain mysteries to this day. The tale is at once a compelling instance of loss on the World War II American home front and a more extensive, largely unreported history. Ponder, a 21-year-old from rural Mississippi and his crew were tragically unexceptional casualties in the monumental effort to recruit and train an air force en masse to counter the global conquest of Nazi Germany and Imperial Japan. More than fifteen thousand American airmen and, in some cases, women burned, crashed, or fell to their deaths in stateside training accidents during the war—their lives and stories shuffled away in piles of Air Force bureaucracy. The forgotten story of Getaway Gertie was originally inspired by summer evenings around the campfire on the shores of Lake Ontario, where parts of the plane have washed up. Building on those campfire tales, the book deftly connects myth with fact and memory with historicity. The result is a vivid portrait of the forgotten soldier of the home front and a new take on the meaning of wartime sacrifice as the last survivors of the Greatest Generation pass away.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.384 | 0.242 |
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".