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Record W4244748182 · doi:10.24124/2014/bpgub1647

A capital budgeting analysis of the proposed Site C Dam

2014· dissertation· en· W4244748182 on OpenAlexaffabout
Tyler Mikkelson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicCapital Investment and Risk Analysis
Canadian institutionsBritish Columbia Institute of Technology
Fundersnot available
KeywordsPayback periodInternal rate of returnCapital budgetingNet present valueProfitability indexCost of capitalEconomicsPresent valueNatural capitalNatural gasRate of returnElectricityCapital (architecture)Capital costFinanceEngineeringMicroeconomicsProduction (economics)MacroeconomicsWaste managementGeographyIncentiveProject appraisal

Abstract

fetched live from OpenAlex

This paper looks at the issues surrounding BC Hydro's the capital budgeting decision for the proposed Site C Dam on the Peace River in northeast British Columbia, Canada. The project is compared with a potential combined cycle natural gas-fired thermal electricity generating facility. Techniques such as net present value, internal rate of return, modified internal rate of return, profitability index, payback period, modified payback period, and equivalent annual annuity are used to evaluate six scenarios. These scenarios have varying values for weighted average costs of capital and carbon tax rates. A sensitivity analysis addressing changes to weighted average cost of capital inflation rate, electricity price, annual electricity output, capital cost, carbon tax rate, and the price of natural gas identifies the largest uncertainties faced by the project and compares them with the natural gas alternative. --Leaf ii.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score0.344

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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 designSimulation or modeling
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
Published2014
Admission routes2
Has abstractyes

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