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Record W2320824601 · doi:10.3720/japt.76.138

Development of extra-heavy oil in the Americas

2011· article· en· W2320824601 on OpenAlexaboutno aff
S. Takada

Bibliographic record

VenueJournal of the Japanese Association for Petroleum Technology · 2011
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessBiddingCorporationInvestment (military)Oil sandsWork (physics)Petroleum industryPetroleumOil reservesNatural resource economicsFinanceAsphaltEnvironmental scienceEngineeringEconomicsGeographyEnvironmental engineering

Abstract

fetched live from OpenAlex

While it is becoming more and more difficult to find new conventional oil fields, the importance of extra-heavy oil in Venezuela and bitumen in Canada has been increasing. Recently, there were two remarkable events occurred in Orinoco development in Venezuela. One is the reserve evaluation project based on inter-government agreements. Some groups have created joint venture companies with PDVSA to enter into development phase after the reserve evaluation work. The other event was the first competitive bidding for Carabobo area development. Two projects were awarded as a result of the bidding process including the project led by Chevron with the participation of JOGMEC, Mitsubishi Corporation and INPEX Corporation. Orinoco development has an advantage over oil sand development in Canada in terms of lower production cost because cold production is the standard method due to relatively low viscosity of oil. However, the severe and unstable investment climate in Venezuela is making it difficult for foreign oil companies to invest in big projects. The development of oil sand in Canada will grow steadily if high oil price continues and appropriate measures are taken to minimize environmental impacts such as carbon dioxide emission, land damage and byproduct disposal. The development of extra-heavy oil in Orinoco, Venezuela can be called as “Frontier” even though certain improvements in investment environment are required to encourage new project startups.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.232

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.272
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2011
Admission routes1
Has abstractyes

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