Bibliographic record
Abstract
Feb. 22nd 1884. My dear Mr. Butler, Your kind letter followed me from Toronto to Quebec, and I have now brought it on with me here; I mean to send it to Goldwin Smith as I know it will give him pleasure to see what you say of him and of his utterances. We have been living in a whirl, and also in the snow, but the interest of Canada is unspeakable and I would not have missed it for the world. Mrs. Arnold has gone through the journey very well has been a great help to me; we travelled from Montreal in one of those “sleepers” which we hate, and slept hardly at all; we arrived here in the middle of the day yesterday, a fine place and a fine people. We had callers all the afternoon, at 6 I dined with some noblemen at the Cumberland Club, then came the lecture on “Numbers” to a great audience, then a crowded reception; and finally a supper-party! However we slept well at last and now we are just starting for Boston where we sleep tonight. I shall e glad of a few hours there to take a last leave of that beautiful city where I have received so much kindness. On Saturday, I go to Albany, & it is finally settled that Mrs. Arnold shall not go there with me, but shall return straight from Boston to the shelter of your hospitable roof – a shelter which I hope to reach on Sunday. My love to Miss Butler in the meanwhile, and believe me, my dear Mr. Butler. Affectionately yours, Matthew Arnold
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.283 | 0.130 |
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".