Bibliographic record
Abstract
[2] Alaska, the adventure on the glacier when the buzzards were looking for you, the Salmon Stories and lots of serious and humorous experience, in short a sort of "Camp-fire talk," even bringing in your "John the Divine" story as sauce to scientific meat This would make a readable mixture of grave and gay. Your memory is chockful of interesting reminiscences of scentific men of [humor?] Dr. John Hall (!) & others which would be interesting and would relieve the seriousness of the purely scientific material. Will you just save the plums for the Century. And by the way have you anything interesting to say of the Klondike? If so, now is your time. Remember that I shall said for London August 21" and let me have a word about this before I leave--or if that isn't possible wirte Mr. Gilder afterward. I suppose you are with Prof. Sargent by this time If so remember me to him cordially. [3] (Muir 2) [letterhead] Why not sit down on receipt of this & sketch out two or three papers of these notes, and see how the thing would look? Could you make one or two Yukon region alone? If so, do it at once. Wasn't the "Alaska Trip" a timely hit, appearing on the very heels of the gold excitement? Heaven favors the virtuous. The Atlantic paper is good & I hear people speak of it. but dont let Page allure you away from your first love. See how we advertise you always as the author of "The Mountains of California". 02323
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.835 | 0.752 |
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".