Bibliographic record
Abstract
We are so inured to events being reported in the news for only a few days; e.g., our diminishing interest in COVID, yet the Battle of the Atlantic lasted five years and eight months, from the sinking of Athenia on 3 September 1939 to the sinking of HMCS Esquimalt on 15 April 1945.There was no sudden climax or turning-point, just waves of successes and losses.Canada lost 24 warships, over 2438 RCN and 752 RCAF personnel in the Battle of the Atlantic (426).Moreover, Allied merchant navies lost 2233 merchant ships (58 being Canadian) and over 30,000 merchant seamen and officers.But there were 25,343 successful trans-Atlantic arrivals in Britain.Over the years, many books have dealt with the Battle of the Atlantic, but most of them paint Canada as having little or no part in the fray.This book has strong Canadian content, not only in the ships involved, but also in the personnel.Barris, an author of many military history books, describes the war not in the impersonal way of ships doing this or that, but through the eyes of both Canadian and German participants.He has interviewed or found the writings of those participants to tell the reader that the battle was fought by people and not by ships and submarines.The book loosely follows the chronological order of events of the battle -the U-boat attacks and the escorts' counter-attacks.It also touches on SS Athenia (torpedoed on the opening day of the war); HMS Royal Oak (torpedoed while at anchor at Scapa Flow); HMS Jervis Bay (took on Admiral Sheer to save its convoy); HMCS Fraser (sliced in half by HMS Calcutta); evacuation at Dunkirk; Britain's gold shipped to Canada; HMS Repulse, a 27,200 T battlecruiser, being "protected" by HMCS Chambly, a 915 T corvette, Book Reviews
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.038 | 0.017 |
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".