Bibliographic record
Abstract
It is fitting indeed that my first message as Colonel-in-Chief of the Royal Newfoundland Regiment should be a foreword to the history of this famous Regiment and its predecessors, covering a period of close on two centuries.My Regiment has the honour of being the only overseas Regiment in the history of British arms to have gained the title of "Royal" during the hostilities in which it was engaged, awarded in recognition of the gallantry and matchless valour displayed on the fields of Gallipoli, France and Belgium in the great struggle for freedom of 1914-18.Well did it deserve this honour.No other Regiment gained this distinction in the First World War, and only twice in former wars were an Irish and an English Regiment similarly honoured.Colonel Nicholson has succeeded splendidly in tracing the long history of the Regiment and in relating its military virtues to the character of the loyal people of Newfoundland, the oldest member of the British Empire and Commonwealth.This book is a record of a fine Regiment, of men of courage and faith who proved themselves worthy of the endurance and devotion of the people among whom they were born and bred.I am very proud to be Colonel-in-chief of my Royal Newfoundland Regiment and to strengthen the ties of comradeship with my Royal Scots (The Royal Regiment).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.044 | 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".