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Record W4381060424 · doi:10.36962/nec18012023-48

Kazakhstan to supply crude oil to Germany

2023· article· en· W4381060424 on OpenAlexaboutno aff
Giorgi Garakanidze Giorgi Garakanidze

Bibliographic record

VenueThe New Economist · 2023
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCrude oilMiddle EastQuarter (Canadian coin)Energy securityPipeline transportEnergy supplyEnvironmental protectionAgricultural economicsBusinessGeographyEnvironmental scienceEngineeringEnvironmental engineeringEnergy (signal processing)EconomicsPetroleum engineeringRenewable energy

Abstract

fetched live from OpenAlex

Kazakhstan has secured approval from Moscow to use its pipeline infrastructure in order to transport 300,000 tons of oil to Germany in the first quarter of 2023, a state-run company (Kaztransoil) announced on January 13, 2023. Deliveries in January, 2023 amounted to 20,000 tons. Kazakhstan plans to export up to 1.5 million tons to Germany via Russia in 2023, but in the future, the volume could be increased to 7 million tons. As for now, oil transportation through Russia seems more beneficial to Kazakhstan, whereas the so-called Middle Corridor transportation route, which involves shipping oil tankers that would cross the Caspian Sea before unloading crude onto freight transport traveling through Azerbaijan, Georgia and Turkey is still limited in capacity and far costlier than using Russian infrastructure. Besides, the ongoing and frozen conflicts in Caucasus could in future endanger the security of Kazakhstan’s oil supply to the EU countries via South Caucasus. Keywords: Kazakhstan, Russia, Germany, Oil, Pipeline, Ukraine, Middle Corridor, Energy Security, Energy.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.024

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2023
Admission routes1
Has abstractyes

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