Bibliographic record
Abstract
While many are familiar with the Normandy Invasion, few American, Canadian or British citizens know about the massive air campaign waged against their occupied ally. This offensive lasted four long years and targeted most of France’s population centers and infrastructure. By the time the war was over, the Allied air forces killed as many French as the Germans killed British civilians during the “blitz” and vengeance weapon assaults, equaling between 60,000 and 75,000 out of a total of 150,000 French civilian deaths during the war were caused by Allied bombs. For Rouen’s civilians the war did not end on June 6, 1944. For more than two months, the city continued to see both the movement of German forces to the front and the continuation of attacks by fighter-bombers. After months of heavy allied bombing, Canadian troops finally moved into Rouen, ending the nightmare. Today, after decades of reconstruction, Rouen is a thriving, vibrant city. It has a beautiful riverfront, great shopping and wonderful cafes and restaurants. However, evidence of the wartime destruction is obvious: damage to the front of the Palace de Justice , the remains of burnt-out buildings, and the noticable differences in the architecture of buildings constructed before and after the war. Justified or not, the devastation of Rouen in 1944 is part of the Second World War’s sordid history. It is certainly a narrative worthy of understanding when evaluating the war’s effect on politics and society in the latter half of the twentieth century.
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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.106 | 0.034 |
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".