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Record W2164652974 · doi:10.1139/l09-060

Backwater calculations for the St. Lawrence Seaway with the first computer in Canada

2009· article· en· W2164652974 on OpenAlexaffvenueabout
Scott M. Campbell

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Geography and Cartography
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectronic computerEngineeringCivil engineeringOperations research

Abstract

fetched live from OpenAlex

As the oldest branch of engineering, it is fitting that civil engineering was the first in Canada to make use of modern computing techniques. In the early 1950s, serious planning was underway regarding the St. Lawrence Seaway and Power Project, but before construction could begin, a lengthy series of backwater calculations was required to predict upriver changes to the water profile. It was estimated that these calculations would have taken 20 person-years to complete by hand, but in 1952 and 1953 Ontario Hydro was able to make use of the first electronic computer in Canada – the Ferut at the University of Toronto – to complete in about eight months. These were the first major calculations carried out on any electronic computer in Canada, and helped prove that an all-Canadian navigation route was possible.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0030.000
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.007

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 head0.006
GPT teacher head0.178
Teacher spread0.172 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations16
Published2009
Admission routes3
Has abstractyes

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