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Record W1994319956 · doi:10.3720/japt.70.125

The diversification of energy source in the new era

2005· article· en· W1994319956 on OpenAlexaboutno aff
Kouichi Iwama

Bibliographic record

VenueJournal of the Japanese Association for Petroleum Technology · 2005
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsDiversification (marketing strategy)ChinaFossil fuelEnergy securityNatural gasPetroleumEconomyEconomicsInternational tradeNatural resource economicsAgricultural economicsBusinessGeographyEngineeringGeologyRenewable energyArchaeologyWaste management

Abstract

fetched live from OpenAlex

I will give you the speech regarding “The diversification of energy source in the new era”. I teach natural resource & energy and industrial organization in Wako University. Both lectures are deeply related to the energy industry. In the present international oil market situations, WTI crude oil prices reached to 50US/bbl in September 2004 and 55US/bbl on October 22 2004, making historical record. The reason is divided to two factors. One is supply side factor which means Middle East unstable situations. Second is demand side factor which is the rapid growth of oil consumption in United States and China. Especially, China's oil consumption made the historical record and became the second largest oil consuming country.However, Japan is still the second largest country in GDP base and has great responsibility to international oil situations. Therefore, we Japanese have to consider the diversification of energy. The diversification of energy includes two factors. One means the utilization of fossil fuel other than conventional oil such as natural gas, Canadian oil sand, methan hydrate and gas to liquid. Second means the diversification of areas such as oil and gas fields of East Siberia, Sakhalin and Azelbaijan. In conclusion, the Japanese contribution regarding the diversification of energy is the improvement of energy security in Japan and Asian countries such as China and India which have carried out the remarkable economic growth using more and more conventional oil.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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 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

Citations3
Published2005
Admission routes1
Has abstractyes

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