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Record W7039610907

Northern lights : a history of Thunder Bay Hydro / by David Leo Black.

2017· other· en· W7039610907 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionTSG101HyporeflexiaLiquationDiafiltrationSubpoena
DOInot available

Abstract

fetched live from OpenAlex

Electricity has played an important role in the economic and social development
\nof Ontario cities, and Port Arthur and Fort William located at the head of the Great
\nLakes are no exception to this rule. Industrial development depended on an adequate
\nelectric power supply, especially for the pulp and paper industry, the industrial mainstay
\nat the Lakehead. Safety in the city streets and a high quality of life for the citizens were
\nalso provided by electric lighting and numerous electric appliances. There are few
\nhouseholds or businesses today that do not have access to electrical power; in this way,
\nit has touched each of our lives. This paper examines the history of the prime provider
\nof electric power at the Lakehead, Thunder Bay Hydro and its predecessors. For one
\nhundred and ten years this area has been served by the hydro electric Commissions of the
\ntwo cities. For the first four decades of their existence, roughly 1910 until the end of the
\nGreat Depression, the Port Arthur Public Utilities Commission and the Fort William
\nHydro-Electric Commission were influenced greatly by the inter-city rivalry. The two
\ncites are geographically isolated from other cities but in close proximity to each other
\nand this set the stage for their rivalry. They competed for such things as industries and
\nelectric power. After the Great Depression began, however this rivalry subsided, where
\nelectric power matters were concerned.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.758
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.009

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 head0.027
GPT teacher head0.228
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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