Charles Stephenson, The Eastern Fleet and the Indian Ocean, 1942-1944: The Fleet that Had to Hide by Mark Klobas
Bibliographic record
Abstract
Reviews 119 negative concepts of society.Readers can expect a humanistic, but also deeply researched analysis of naval battles.For example, the study of the Battle of Actium (31 BC) recounts the relationships and dramas between Mark Antony, Cleopatra, Cesar Augustus, and Rome that surrounded the battle.This was the story that captured the attention of another author named Shakespeare in another time, prompting him to dramatize the history for theatre.Russell also depicts the struggles of a young Commodore Nelson, a rising naval star, who, at 41 years old, had already sacrificed an eye and an arm fighting for the Royal Navy.He draws brilliantly from the life of Nelson and his mission of "search and destroy," revealing the intrinsic anxiety of the endless "search" while emphasizing his genius, his insecurities, his bravery and his little note to Lady Hamilton.The reader can find these subtle, peculiar and delicate details on every page.The weaker aspects of the book are, firstly, the maps that are located in the initial pages and not among the narratives, which forces the reader to flip back and forth.Secondly, this is not an introductory book: beginners in the naval strategy/history field may find some difficultly with the prolonged details of battles and historical contexts.This, however, makes the book perfect for researchers, especially those in search of more material about ancient naval battles.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".