Bibliographic record
Abstract
[1] [letterhead] Oct 18 1898 Dear Wanda & Helen & Mamma Im pretty sleepy, for it was after midnight when I went to bed last night & the bed was only a confounded stuffy jiggling bunk at the top of a sleeping or sleepless car. But this day was so crisp & bright & delightful, so full of lovely & wild scenery it might awaken the dead & do away with sleep altogether. I stopped here on my way from Montreal to the White Mountains & all the scenery was beautiful & must be beautiful all the year but robed with glorious leaf colors as it is now nobody can half tell or even hint it. The town is finely 02486 [2] situated on Lake Champlain on high ground on the Eastern shore commanding wide views of the lake with its many islands & the mountains of the Adirondacks region, while the Green Mountains make a grand fence along the Eastern horizon. I got here about noon, had a nice dinner in a fine clean commodious hotel [in margin: 50] which you may be sure I appreciated after the squalled piggy places we had to stop at in the southern states. Then I got a buggy & drove through the pretty town & the hills & along the lake through the midst of Yellow & purple & golden trees & bushes. My! If you & Helen & Mamma could have been with me. Tomorrow I start for Stowe & thence up Mt Mansfield. Thence I go to Mt Washington & the passes and notches of the White Mountains, & 02486
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.862 | 0.804 |
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".