Bibliographic record
Abstract
From 1939 to 1941, circumstances handed the Wehrmacht a perfect opportunity to fight Bewegungskrieg : short, sharp campaigns within the friendly confines of central and eastern Europe, with its relatively short distances, temperate climate, and highly developed road and rail infrastructure. When it came to operational-level maneuver warfare under these conditions, the Wehrmacht was without peer. None of this was new in Prussian or German history, and indeed the exact same description might be applied to Prussian armies under Frederick the Great. The summer of 1941 saw the opening of the war’s main event. Operation Barbarossa was the greatest undertaking in military history, and German success in the opening weeks was amazing. With the Panzers ranging far and deep, the Wehrmacht sealed off one immense encirclement of Soviet forces after another: at Bialystok, Minsk, Smolensk. By December, the Germans stood outside Moscow. They had inflicted four million casualties on the Red Army, about 3 million of whom were prisoners, and to many observers, the Soviet Union seemed finished. Indeed, Germany had conquered the continent. What we might call the “Great European War” of 1939-41 was over. It was the war that Hitler won.
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 | 0.001 |
| 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 | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".