81 days below zero : the incredible survival story of a World War II pilot in Alaska's frozen wilderness
Bibliographic record
Abstract
"Shortly before Christmas in 1943, five Army aviators left Alaska's Ladd Field on a test flight. Only one ever returned: Leon Crane, a city kid from Philadelphia with little more than a parachute on his back when he bailed from his B-24 Liberator before it crashed into the Arctic. Alone in subzero temperatures, Crane managed to stay alive in the dead of the Yukon winter for nearly twelve weeks and, amazingly, walked out of the ordeal intact. 81 Days Below Zero recounts, for the first time, the full story of Crane's remarkable saga. In a drama of staggering resolve with moments of phenomenal luck, Crane learned to survive in the Yukon's unforgiving landscape. His is a tale of the human capacity to endure extreme conditions and intense loneliness-and emerge stronger than before. "..
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.025 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".