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Record W2658610679 · doi:10.1299/jsmepes.2010.15.473

F206 Enhanced methane hydrate recovery using exothermic heat of CO_2 hydrate formation, experimental verification of an principle of continuous CO_2 injection into formations

2010· article· en· W2658610679 on OpenAlexaboutno aff
Yojiro Ikegawa, Kimio Miyakawa, Kouichi Suzuki

Bibliographic record

VenueDoryoku, Enerugi Gijutsu Shinpojiumu koen ronbunshu/Doryoku, enerugi gijutsu no saizensen koen ronbunshu · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsMethaneHydrateExothermic reactionClathrate hydrateNatural gasCabin pressurizationEnvironmental sciencePetroleum engineeringMaterials scienceChemical engineeringMineralogyGeologyWaste managementChemistryEngineeringComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

The amount of methane hydrates in our marine sediments is reported about 4.65 to 7.35 trillion cubic meters. Our yearly natural gas consumption is 820 billion cubic meters. Japan national research succeeded to demonstrate methane hydrate recovery in Canada by the depressurization method. A demonstration in Nankai trough is planned for the next step. CRIEPI has proposed a methane hydrate enhanced recovery method by using exothermic heat of CO_2 hydrate formation to improve the productivity and the recovery factor. This enhanced recovery can be adapted for sediments less than 10 degrees centigrade. The number of the sites is two-thirds of the founded sites in the world.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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 designBench or experimental
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
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueDoryoku, Enerugi Gijutsu Shinpojiumu koen ronbunshu/Doryoku, enerugi gijutsu no saizensen koen ronbunshu→Same topicMethane Hydrates and Related Phenomena→French-language works237,207→