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Record W2356772320

Jiangxi Shale Gas Resources Situation and Exploration Prospect

2013· article· en· W2356772320 on OpenAlexaboutno aff
Xia Xiaoji

Bibliographic record

VenueEnergy Research and Management · 2013
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsOil shaleShale gasGeologyPetroleum engineeringMining engineeringUnconventional oilGeochemistryPermianEarth sciencePaleontology
DOInot available

Abstract

fetched live from OpenAlex

Shale gas is a clean,efficient of unconventional gas resources.With the breakthrough of shale gas exploration and development technology,United States and Canada develop rapidly in shale gas.Our country has introduced advanced technology and theory continuously,to prospect domestic large area shale gas.Through investigation,thinks the lower Cambrian,lower Silurian,middle Permian shale are widely developed,and have the geological conditions of forming shale gas.Contrast Jiangxi under lower Cambrian shale with domestic and overseas,get the conclusion that Jiangxi shale reservoir has good geological conditions,great potential for shale gas accumulation.Shale gas are mainly distributed in northeast Jiangxi,northwest Jiangxi,Pingxiang-Leping depression and southern Jiangxi,preliminary estimates shale gas geology resources of Jiangxi province reach up to(3.5~7.0)×1012m3.Shale gas resources in Jiangxi have great potential,with good prospects for exploration and development.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.252
Teacher spread0.226 · 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 designObservational
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
Published2013
Admission routes1
Has abstractyes

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