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Record W4236054408 · doi:10.4324/9781351211628-39

W. S. Caine, A Trip Round the World in 1887–8 (London: G. Routledge & Sons, 1888), pp. 92–118

2020· book-chapter· en· W4236054408 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldArts and Humanities
TopicHistory of Science and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

On Monday, September 19th, we were roused from our beds at 4 o’clock A.M., as the westward bound daily train passed through Banff at five o’clock. At the station we met with the only instance of neglect of duty on the perfectly-ordered Canadian Pacific Railway. The station-master did not condescend to leave his warm bed to see the train off, and we had to carry our luggage ourselves from the omnibus to the luggage car, and let them go on unchecked to Field, our next stopping place. It was a cold, sleety morning, and the magnificent scenery through which we passed was not seen to the best advantage, as the tops of the mountains were enveloped in snow clouds. At seven we passed a station called Silver City. Three or four years ago there was a “boom” in silver mines in the Rocky Mountains; a good deal of exploration went on, and a considerable wooden village was built. But there was no “silver,” and now there is no “city.” Its glory has departed, and only the empty and deserted log-houses remain to tell of its butterfly existence. Shortly after, Mount Lefroy, a commanding snowy peak 11,658 feet above sea-level, comes into view, and presently the birthplace of the noble Bow River is discerned in a small glacier wedged in between Mount Hector and Goat Mountain, both over 10,000 feet. Then the highest point of the railway is reached, 5,300 feet above the sea, at the summit lake, marshy and shallow, from which trickles a stream at each end, one of which travels 2,000 miles to the Atlantic, and the other 1,500 to the Pacific Ocean. We now bid good-bye to the beautiful Bow River, which has been our genial companion for so many pleasant days, and under the shadow of Mount Stephen, the monarch of the Rocky Mountains, said to be over 12,000 feet, and named after the president of the Canadian Pacific Railway, we enter Kicking Horse Pass. This pass received its ridiculous name from an incident connected with some obstreperous horse ridden by one of the surveyors of the line, which will stick to it for ever. A magnificent view meets the gaze. A huge valley, filled from side to side with magnificent pines and cedars, their dark green intensified by the red-brown of huge areas burnt up by forest fires, in which the enormous trunks stand up like black masts 200 feet high, and 10 or 12 feet thick, 267 is flanked by peak and pinnacle, the Kicking Horse River meandering through the bottom like a silver ribbon. The train, with two powerful engines reversed, and every brake screwed to its tightest, slides down a gradient of 1,250 feet in less than 10 miles. The road is cut out of the sides of great cliffs, hundreds of feet above the roaring torrent, and every now and then we crawl over a trestle bridge two or three hundred feet above some gorge torn out of the mountain side by a rushing torrent. At nine o’clock we draw up at Field Station, a lonely post in the heart of the Rocky Mountains, where the Canadian Pacific Railway Company have built a comfortable little hotel, at which we decide to stay for 24 hours. It was a great comfort to know, as we came down this terrible descent, that we were travelling on rails made from good honest Cumberland Hæmatite. I have noted, with interest, but without surprise, that the word “Barrow” always appeared on the rails which the Canadian Pacific Railway have laid down in dangerous places, or where there is specially heavy wear and tear.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.196
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0050.003
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1250.042

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.

Opus teacher head0.067
GPT teacher head0.247
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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