Bibliographic record
Abstract
W hen the companions of the explorer Cartier found that the rapids at Montreal were not the end of all navigation, as they had feared, but that above them there commenced a second and boundless reach of deep, still waters, they fancied they had found the long-looked-for route to China, and cried, “La Chine!” So the story goes, and the name has stuck to the place. Up to 1861, the Canadians remained in the belief that they were at least the potential possessors of the only possible road for the China trade of the future, for in that year a Canadian government paper declared that the Rocky Mountains, south of British territory, were impassable for railroads. Maps showed that from St. Louis to San Francisco the distance was twice that from the head of navigation on Lake Superior to the British Pacific ports. America has gone through a five years’ agony since that time; but now, in the first days of peace, we find that the American Pacific Railroad, growing at the average rate of two miles a day at one end, and one mile a day at the other, will stretch from sea to sea in 1869 or 1870, while the British line remains a dream. Not only have the Rocky Mountains turned out to be passable, but the engineers have found themselves compelled to decide on the conflicting claims of passes without number.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.055 | 0.012 |
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".