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Record W4385976081 · doi:10.5267/j.uscm.2023.7.001

Can the Arab’s natural gas secure the Europeans’ gas requirements? the case of liquified natural gas (LNG)

2023· article· en· W4385976081 on OpenAlexvenueno aff
Abdulkarim Ali Dahan, Rasha A. Altheeb

Bibliographic record

VenueUncertain Supply Chain Management · 2023
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsNatural gasLiquefied natural gasDestinationsEconomicsSupply and demandInternational tradeBusinessEnvironmental economicsNatural resource economicsMicroeconomicsEngineeringWaste management

Abstract

fetched live from OpenAlex

This article examines the possibility of answering the question” can the Arab’s natural gas secure the gas requirements in Europe? “To answer the question, an economic analysis of natural gas was conducted to examine reserve, supply, demand, and international trade first. Second, an economic model to examine distances and transportation costs, for transferring goods from various points of supply to various points of demand, was adopted. The North-West Corner model approach, a QM for Windows-based economic strategy to solve the transportation model problem structure in linear programming, has been used in this regard. Our findings demonstrate that the model is suitable for application since it provides the least distances and the least transportation costs compared to other alternatives. The model estimated that a cost of $309.41 is required to transfer one MMBtu of LNG from origins to final destinations. A decrease of $34.304/MMBtu, 10%, compared to $343.714 /MMBtu. It is concluded that the Arab’s gas could fulfil gas requirements in Europe, and mutual benefit can be accomplished for both parties. European countries will benefit from acquiring new places with less distances and lower delivery costs, and Arab countries would have the chance to get new consumers and play a role in the market given their collective gas reserves and their advantageous strategic locations.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.018
GPT teacher head0.259
Teacher spread0.241 · 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 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

Citations4
Published2023
Admission routes1
Has abstractyes

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