A witness in the landscape: The bombing of the Forêt domaniale des Andaines and the Normandy Campaign, NW France, 1944
Bibliographic record
Abstract
An archaeological survey of well-preserved Second World War German supply depots and bomb craters from Allied air raids in the Forêt domaniale des Andaines, Normandy, has prompted an evaluation of the effectiveness of Allied intelligence gathering and tactical bombing of the German logistics network in advance of, and during the Normandy Campaign of June–August 1944. In conjunction with analysis of primary German and Allied archive sources, published historical accounts and aerial photographs, we demonstrate that Allied intelligence knew of the importance of the forest as a major fuel depot and attacked it with at least 46 missions over the period 13 June–4 August. However, landscape evidence demonstrates that only one of three fuel depot sites in the forest was successfully identified and partially destroyed by bombing. Allied intelligence efforts also failed to gather sufficient evidence to target one of the largest Seventh Army munitions depots in Normandy. Supply depots in the forest thus remained operational until late in the campaign and will have supported the German Mortain counter-offensive of 7–14 August. The limited success of Allied bombing in the Forêt domaniale des Andaines testifies to the difficulties in striking well-dispersed and camouflaged woodland facilities and supports the argument that the success of air power against German logistics efforts lay primarily in the degradation of the regional communications infrastructure and the Wehrmacht’s vehicle fleet rather than the destruction of supply dumps.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".