Bibliographic record
Abstract
When the district [New Caledonia] was first settled [by the NWC in 1805], the goods required for trade were brought in by the winterers [wintering partners] from Lac la Pluie [Fort Frances on Rainy Lake], which was their depot.The people left the district as early in spring as the navigation permitted, and returned so late that they were frequently overtaken by winter ere they reached their destination.Cold, hunger, and fatigue, were the unavoidable consequences; but the enterprising spirit of the men of those days -the intrepid, indefatigable adventurers of the North-West Company -overcame every difficulty.It was that spirit that opened a communication across the broad continent of America; that penetrated to the frost-bound regions of the Arctic circle; and that established a trade with the natives in this remote land, when the merchandise required for it was in one season transported from Montreal to within a short distance of the Pacific.Such enterprise has never been exceeded, seldom or never equalled.The outfit is now [middle 1830s] sent out from England by Cape Horn, to Fort Vancouver, thence it is conveyed in boats to [Fort] Okanagan, then transported on horses' backs to Alexandria, the lower post of the district, whence it is conveyed in boats to Fort St. James.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.423 | 0.177 |
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".