Xiaobing Li, China’s New Navy: The Evolution of PLAN from the People’s Revolution to a 21st Century Cold War
Bibliographic record
Abstract
The Northern Mariner / Le marin du nord the First World War.After a series of engagements between battlecruisers and detached battleships, the two opposing columns of dreadnoughts bore down on each other, the Germans finding themselves in a disadvantageous tactical position because the British were "crossing the T," which allowed them to fire full broadsides with all guns while not under the full weight of opposing fire.Sensing a trap, the German Admiral Reinhard von Scheer ordered the High Seas Fleet to turn away that put distance between them and the Grand Fleet while the battlecruisers and torpedo boats attacked in mass as cover.The German High Seas Fleet survived to remain a fleet in being but never really sortied again in force.The naval war instead shifted to submarines on the German side in 1917 and 1918.Maintenance of the German High Seas Fleet in a state of readiness until the end of the war tied up scarce personnel and material resources, and finally, in the face of defeat and starvation, German sailors mutinied in 1918.This offering in Osprey's Fleet series provides a very readable and visually pleasing primer on the German High Seas Fleet.A number of key battles are highlighted in text and graphics.The affordable book is recommended for readers interested in First World War naval operations, German naval developments pre-1918, and as a naval history reference source for wargaming and scale modelling.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".