Bibliographic record
Abstract
that fatal breath of 'improvement'" Graeme Wynn W hen the Canadian Pacific Railway began carrying passengers through the western mountains in 1886, the "awful grandeur" of the rugged terrain west of Calgary became the focus of much admiring attention, not least by agents of the railroad, anxious to recoup enormous construction costs by capitalizing on the scenery through which the rails ran.Given impetus by the country's first prime minister, who was persuaded, after an early trip along the transcontinental line, that although "there may be monotony of mountains as there may be prairies … in our mountain scenery there is no monotony," a concerted publicity campaign "sold" the region to the world. 1 The Canadian Rockies were a titanic sculpture.Here "serrated peaks, and vast pyramids of rock with curiously contorted and folded strata" were "followed by gigantic castellated masses down whose sides cascades fall thousands of feet."Glimpses of "glaciers and other strange and rare sights" were available from the luxury of the railway's Pullman cars. 2 Fine fishing and magnificent shooting could be had a short distance from one or another of the stops along the CPR line.Glacier House offered accommodation at the foot of the Illecillewaet Glacier, in the shadow of a peak considered the equivalent of "a dozen Matterhorns," and by century's end Swiss guides were employed there to lead climbers into the mountains, sometimes described in promotional literature as constituting "fifty Switzerlands in one." 3 At Banff, which Prime Minister Macdonald believed beyond compare in its combination of "so many attractions" and its possession of "all of the qualifications necessary to make it a great place of
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.774 | 0.765 |
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".