Bibliographic record
Abstract
Jean was 3/4 when war broke out. At 5 years old (her sister was 7), in May 1940, she went to boarding school - St Anne's, Windermere. Dad was a doctor with Nigerian Medical Service. In Northern Ireland when war broke out. In 1944 Dad came back with a big trunk - whole bottom was filled with Dutch sweets - stroop waffles. Mum went from London to Paris in 1940 and stayed the night three days before Paris fell. Mum worked in a medical clinic. In 1942 parents came home. Mum couldn't come because convoys were being torpedoed. Grandparents on Mother's side during bombing raids/air raids 'sat under the table and hoped it wouldn't land on you'. Aunt sent eggs wrapped in cotton wool through the post.Black market for food due to rations. At ten years of age would cycle 25 miles to the Methhodist Chapel.Wrote to parents every Sunday. Matron Gibbs was lovely and called 'roly poly'. Miss Jux the music teacher was mean. Clothing was out of stock - hand me downs. Goose grease rubbed on chest to try to prevent/cure illness.Shorts flying boats built on Lake Windermere.During air raid warnings you would go under the stairs.Flew in 6 seater plane to Belfast from Liverpool with Mum, Dad and her sister, Flying fortress - taxied under wing.1948 - 10 passengers, 7 crew, Halton converted Halifax Bomber - barley sugars to suck, cotton wool for ears, notepad because too loud to speak.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.158 | 0.037 |
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".