Bibliographic record
Abstract
Ronald Taylor was born in a small Welsh village, Talywain, in 1922. He was the first born of six boys to Dorothy and Wilfred Taylor. Ronald had just turned 20 years old when he joined the Royal Navy in March 1942. He was trained as a Gunner. Before he went to sea he returned home to his family for a short visit. My father, who was 10 years old at the time, recalled walking with Ronald back to the village train station carrying his cloth rucksack and on saying goodbye Ronald gave him a piece of his lapel string to keep safe till he returned. On returning to Portsmouth Ronald served on the ship Glendower, the Wellesley and finally he boarded the Otina in December 1942. This ship was part of a convoy of 43 ships, which was part of the British escort group B7 consisting of the Destroyers Firedrake and Ripley and the corvettes Sunflower, Loosestrife, Alsima and Pink. They were travelling through the North Atlantic, from Belfast to New York. A quarter of the way through their journey they were stalked by a German "Wolf Pack" ( a group of German submarines). On the night of the 21st December at 21.00 hours his ship was torpedoed twice and within 45 minutes the ship sank killing all 60 crew members. Ronald was one of seven Royal Navy Gunners on board.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.173 | 0.067 |
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".