A Tour through Wales: in a Letter from a young Lady—
Bibliographic record
Abstract
My dear Clara I have been so long on the ramble that I have not till now had it in my power to thank you for your Letter—.We left our dear home on last Monday Month; and proceeded on our tour through Wales, which is a principality contiguous to England and gives the title to the Prince of Wales. We travelled on horseback by preference. My Mother rode upon our little poney and Fanny and I walked by her side or rather ran, for my Mother is so fond of riding fast that She galloped all the way. You may be sure that we were in a fine perspiration when we came to our place of resting. Fanny has taken a great Many Drawings of the Country, which are very beautiful, tho’ perhaps not such exact resemblances as might be wished, from their being taken as she ran along. It would astonish you to see all the Shoes we wore out in our Tour. We determined to take a good Stock with us and therefore each took a pair of our own besides those we set off in. However we were obliged to have them both capped and heelpeiced at Carmarthen, and at last when they were quite gone, Mama was so kind as to lend us a pair of blue Sattin Slippers, of which we each took one and hopped home from Hereford delightfully— I am your ever affectionate Elizabeth Johnson.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.094 | 0.031 |
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".