Bibliographic record
Abstract
St. Michael, Alaska Aug. 31st, 1899. My Dear Friend Muir: I have just arrived in the [illegible] after an eventful & busy summer in the valley of the great Yukon. I was delayed a month in all at Skagway, more than a week after I saw you. Then I went over to Bennett, bought a Klondyke boat & Mr. Koonce navigated it with our nearly three tons of goods down to Ra[illegible]. It was the first week in July before we arrived at our first camping place, where we were to remain any time, - Eagle, just across the line in Alaska, I went at once into the woods to try to get you the cone blossoms you wished. But it was evidently far beyond the time. I chopped down a number to trees, but the cones were hardened, the blossoms gone. I am very sorry - will try to do better next summer. I have found only three species of evergreen trees in the Yukon Valley. You can best name them - two species of spruce & a fir. But I saw some wonderful country. I took one eighty mile walk across the mountains, ascending America Creek from Eagle 18 miles, then across the mountain ridges to Comet Creek which empties into Forty mile, camped in the basin of grand rugged edged mountains, the [illegible] of mountain sheep, lived three days on grayling, then across the ridges & rugges mountain slopes 02615
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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.883 | 0.844 |
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".