Bibliographic record
Abstract
Sir John Duckworth commanded ships and squadrons and fleets throughout the Revolutionary and Napoleonic wars. He was an assiduous correspondent, writing to Admirals St Vincent, Nelson, Collingwood, and numerous other naval officers. He kept every piece of paper he wrote on or received. He was in the first expedition to the West Indies when he went on a mission to the United States to suppress a French privateer. He commanded a ship in First of June fight in 1794, and was peripherally involved in the great naval mutinies of 1797. He was picked out by Lord St Vincent to command the recovery of Minorca in 1798. He returned to the West Indies in 1799 where he was commander-in-chief in the Leeward Islands, and then at Jamaica. There he was much involved in the Revolutionary war in Haiti, eventually receiving several thousands of French refugees and sending them on to France. A spell with the Channel fleet was succeeded by time at the blockade of Gibraltar. Against orders, he chased a French squadron across the Atlantic and destroyed it (Battle of San Domingo 1796). One of his more curious adventures was a diplomatic mission to the Constantinople to browbeat the Ottoman Sultan into making peace with Russia in 1807. He failed, of course, and was criticised for not bombarding the city. He served out his time afloat with the Channel fleet, displaying his usual humanity. A three-year appointment as governor of Newfoundland completed his career.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.181 | 0.098 |
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".