MétaCan
Menu
Back to cohort
Record W2343349455 · doi:10.14288/1.0095052

The value of British Columbia’s natural gas used as liquefied natural gas (LNG) for export to Japan

2010· article· en· W2343349455 on OpenAlexaboutno aff
François Dionne

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLiquefied natural gasNatural gasNatural (archaeology)Waste managementValue (mathematics)Natural gas fieldEnvironmental scienceEngineeringGeographyArchaeologyMathematics

Abstract

fetched live from OpenAlex

The objective of this thesis is to determine the value of British Columbia's natural gas used as liquefied natural gas (LNG) for export to Japan. This value is calculated by a computer model simulating an LNG project in B.C. The model starts with an estimate of the landed price of LNG in Japan and works backward, costing every step, to the input-end of the pipeline delivering the natural gas from the field to the liquefaction plant. The value obtained is the opportunity cost of the natural gas used as LNG and can be compared to the opportunity cost in other uses and to the cost of supplying the natural gas. We calculate this value for both society and the private firm - the difference accounted for by the particular tax structure which would apply to an LNG export project. The base case estimates of the social opportunity cost of the natural gas used as LNG range from $3,645 to $4.12 (1981 Canadian dollars) per thousand cubic feet (MCF), depending on the scale of the liquefaction plant. The estimates of the private opportunity cost are very close to the social values - a difference of about 3%. A comparable estimate for the opportunity cost in use as exports to the United States by pipeline is $4.68/MCF although this figure is based on present and not potential contracts. A sensitivity analysis is performed and the capital cost and the landed price are found to be the variables with the largest relative impact on the base case estimates.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.193
Teacher spread0.187 · 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 teacher head, not a consensus.

Study designOther design
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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)Same topicGlobal Energy Security and PolicyFrench-language works237,207