The soldiers' general Bert Hoffmeister at war
Bibliographic record
Abstract
"Self-doubt so plagued him that he suffered a nervous breakdown even before fighting his first combat action. But by the end of the Second World War, Bert Hoffmeister had exorcised his anxieties, risen from Captain to Major-General, and won more awards than any other Canadian officer in the war. Fighting from the invasion of Sicily in July 1943 to the final victory in Europe in May 1945, this native Vancouverite earned a reputation for being a fearless commander on the battlefield, one who led from the front, one who led from the front and was well loved by those he commanded. How did he do it?" "The Soldiers' General explains how Hoffmeister conducted his business as a military commander. Douglas Delaney dissects Hoffmeister's numerous battles to reveal how he managed and how he led, how he directed and how he inspired. An exemplary leader, Hoffmeister stood out among his contemporaries not so much for his technical ability to move the chess pieces well as for his ability to get the chess pieces to move themselves."--BOOK JACKET.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.147 | 0.058 |
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".