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Vanishing Point

2023· book· en· W4386971504 on OpenAlexaboutno aff
Tom Wilber

Bibliographic record

VenueCornell University Press eBooks · 2023
Typebook
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsFellHistorySpanish Civil WarAncient historyMythologyNazismBureaucracyArt historyWorld War IIFront (military)EngineeringCartographyArchaeologyLawGermanClassicsPoliticsGeography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.870
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.080
GPT teacher head0.258
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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