The war we won apart the untold story of two elite agents who became one of the most decorated couples of WWII
Bibliographic record
Abstract
"Love, betrayal, and a secret war: the untold story of two elite agents, one Canadian, one British, who became one of the most decorated wartime couples of WWII. On opposite sides of the pond, Sonia Butt, an adventurous young British woman, and Guy d'Artois, a French-Canadian soldier and thunderstorm of a man, are preparing to go to war. From different worlds, they make their way to fight in Winston Churchill's secret army against the German forces and, unlike most involved in the world's deadliest conflict to date, to fight from behind enemy lines. Their lives first intersect during clandestine training to become agents with the Special Operations Executive. Sonia and Guy learn how to parachute into enemy territory, how to kill, blow up rail lines, support the French resistance, and eventually...how to love each other. But not long after their hasty marriage, their love is tested by separation, by a titanic invasion--and by indiscretion. Written in vivid, heart stopping prose, we follow their stories of uncommon courage--as Sonia plunges into Nazi-occupied France and slinks into black market restaurants to throw off German forces who knew she'd arrived, while at the same time participating in sabotage operations against them by night; and as Guy, in another corner of France, trains hundreds into a resistance army, fashioning himself a military leader, weapons instructor, and peacemaker all at once. Reconstructed from hours of unpublished interviews and hundreds of archival and personal documents, Ayed tells a story of sacrifice and youthful folly; a story about the ravaging costs of war paid for disproportionately by the young. But more than anything, The War We Won Apart is a story about love: two secret agents who were supposed to land in enemy territory together, but were fated to fight the war apart."--
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.035 | 0.016 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".