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Record W2730780787 · doi:10.1111/opec.12104

The causal relationship in North American energy production

2017· article· en· W2730780787 on OpenAlexaboutno aff
Neil A. Wilmot, Ariuna Taivan

Bibliographic record

VenueOPEC Energy Review · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsNatural gasContext (archaeology)Production (economics)CointegrationFossil fuelNatural resource economicsHydraulic fracturingNatural gas pricesEconomicsOil and natural gasCrude oilEnergy marketPetroleum engineeringEconometricsGeographyRenewable energyEngineeringMacroeconomicsWaste management

Abstract

fetched live from OpenAlex

Abstract Crude oil and natural gas production is examined to investigate the cross‐country causal relationship and interconnectedness of these markets, within the North American context. A vast infrastructure network, consisting of pipelines and railroads that connect the US and Canadian markets, with virtually all of Canada's crude oil and natural gas exports flowing south. The study is undertaken within the context of the recent US shale energy revolution based on technological advancements in drilling and hydraulic fracturing. Unique to this study is the use of production data, rather than the archetypal energy prices, to investigate the presence of bilateral relationships. Monthly, country level data on crude oil and natural gas production, over the period 2002 through 2015, is utilised. The results of standard unit root tests indicate that the production series are non‐stationary in levels, while cointegration test indicate that the markets are integrated. A bidirectional relationship is found for the crude oil market. In contrast, a unidirectional relationship is observed in the gas market – US natural gas production causes Canadian natural gas production.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.835
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.257
Teacher spread0.216 · 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 designObservational
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

Citations2
Published2017
Admission routes1
Has abstractyes

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