Britain's forgotten battle the Reichswald forest campaign, 1945
Bibliographic record
Abstract
"On 8 February 1945, over 50,000 British and Canadian soldiers moved forward to attack German defensive positions centred on the vast Reichswald Forest, in what proved to be one of the last and bloodiest battles of the whole of the Second World War in Europe. The Reichswald (German Imperial Forest) on the Rhineland borders of the Netherlands and Germany became the location of an epic struggle that eventually sucked in over 200,000 British and Canadian service personnel. The campaign, sandwiched between better-known clashes such as 1944's Battle of the Bulge and the crossing of the Rhine in 1945, was brutal. The Allies suffered nearly 16,000 casualties, the Germans an estimated 44,000. Drawing on a wealth of sources from British, Canadian and European museums and archives, the authors provide a new and timely account - on the 80th anniversary - of this epic British and Canadian struggle against the Wehrmacht, fought out on the north-eastern borders of Germany during the dying days of the war in Europe."
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".