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Record W3039325686 · doi:10.37867/te100102

AN ANALYSIS OF POWER SECTOR REFORMS IN INDIA AND CANADA

2018· article· en· W3039325686 on OpenAlex
Hetal Chokshi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTowards Excellence · 2018
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
FundersManitoba Hydro
KeywordsHydroelectricityElectrificationHydropowerNova scotiaElectricityRural electrificationElectric power industryGeographyEconomyAgricultural economicsEngineeringArchaeologyEconomics

Abstract

fetched live from OpenAlex

The electricity generation in Canada uses natural resources more. At present too, almost 65% of electricity is generated by hydro plants. The Nelson Electric Light Company, the first company to build a hydro site in British Columbia commenced its operation producing power for the City of Nelson on February 1, 1896. The Sandon plant was the second in March 1897. Development of the electricity sector gathered momentum after the First World War with the creation of provincial utilities in Nova Scotia, New Brunswick, Manitoba, Saskatchewan and British Columbia in the 1920s. Publicly owned electric companies emphasised mainly on rural electrification and hydroelectric development. In Manitoba and British Columbia, private companies repaidly developed the hydropower. Since 1960, large hydroelectric projects, mainly in Quebec, British Columbia, Manitoba and Newfoundland and Labrador, significantly increased the country's generation capacity

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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