Bibliographic record
Abstract
My stretcher is one scarlet stain, And as I tries to scrape it clean, I tell you what - I'm sick of pain, For all I've heard, for all I've seen; Around me is the hellish night, And as the war's red rim I trace, I wonder if in Heaven's height Our God don't Written [down] by Thomas Albert Crawford (my father) who served with the 15th DLI. Tommy was injured on 1st July 1916 on the Somme. He survived the war only to lose his wife (from cancer) and his two sons in their early 30's. Tommy re-married and had two sons, Colin and Brian. Colin died at 25 years of age and six months later in 1980 Tommy passed away. I have recently puslished Tommy's memoirs entitled "Tommy" available from Woodfieldpublishing.com - all royalties go to the Commonwealth Graves Commission. Editor's Comment: Pte. 28695 Thomas Albert Crawford, 15th (Service) Bn. Durham Light Infantry (later Labour Corps, service no. 123884). The 15th Bn. was part of the 21st Division, which arrived in France in September 1915. The division attacked Fricourt on the 1st July 1916, the first day of the Battle of the Somme (in which action Pte. Crawford was wounded). The poem 'The Stretcher Bearer' was written by Robert William Service, a British-Canadian poet and writer. It was published in 1916 in his book 'Rhymes of a Red-Cross Man' (Toronto: William Briggs, 1916). See https://en.wikipedia.org/wiki/Robert_W._Service.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.526 | 0.384 |
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".