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Record W6987487802

Summer tours and excursions on the Intercolonial Railway of Canada, the popular and scenic route for summer travel.

2014· article· en· W6987487802 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Period (music)TourismField (mathematics)
DOInot available

Abstract

fetched live from OpenAlex

SOMETHING ABOUT EXCURSIONS.4< Ah!" sighs the dreamer, "would that such a lot were mine.Such places there may be, but where are they?My guidebooks (ell not of them.To find them, one must abandon the comforts of daily life, go far beyond reach of daily mails and telegrams, become isolated from the busy world, and live hundreds of miles from the confines of civilization."Not so.You have perhaps been down the St. Lawrence as far as Quebec, from which, as the Ultima Thule of your excursion, you returned to your home.Take your map and trace that line which leads from Quebec down the St. Lawrence, across to New Brunswick, and down its coast to Nova Scotia, where it ends at the City of Halifax.To the east and west, arms reach out to Pictou, Sydney and St. John, and another branch traverses Prince Edward Island.This is the Inter- colonial Railway, "The People's Railway," one <>f the most substantially constructed and best equipped lines in the world.It runs through hundreds of miles of just such a country as has been mentioned.Pleasure and sport may be enjoyed in numberless places and yet the traveller will be within the reach of daily mails and the telegraph, and may live like a prince at a very moderate outlay.It is the land for which you have sighed.; try it anil be convinced.

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)0.000
metaresearch head score (Gemma)0.001
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: Other
Teacher disagreement score0.169
Threshold uncertainty score0.566

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1690.027

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 head0.012
GPT teacher head0.173
Teacher spread0.162 · 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
Published2014
Admission routes1
Has abstractyes

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