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Record W7099826804

Steel Manufacturers at the Margin in Nova Scotia

2013· article· en· W7099826804 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicDutch Social and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaIron oreSteel millMargin (machine learning)Pig iron
DOInot available

Abstract

fetched live from OpenAlex

fnwood At the end of the 1890s the Canadian economy began to expand and diversify at an unprecdented rate [$4, p. 55]. Prominent among the changes was an enormous expansion of iron and steel output [19]. The largest single contribution to Canada's iron and steel "takeoff " came from a 1,000-ton-per-day plant at Sydney, Nova Scotia. This plant relied hea•41y u•on ore from a mine located on Bell Island, Newfoundland. Because of its mec•ocre quality, the ore lay idle until technological change expanded the range of workable resources at the very end of the nineteenth century. Although technical progress brought steel manufacture with Newfoundland ore inside the margin of profitability, the Sydney steel plant continued to be handicapped by the poor quality of its resource base. Iron was known to be present on Bell Island at least as early as the 1570s, during which decade ore samples were sent to England [29]. During the early 1600s detailed plans were made to mine and smelt the

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 categoriesInsufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.026
GPT teacher head0.283
Teacher spread0.258 · 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
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

Citations0
Published2013
Admission routes1
Has abstractyes

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