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Record W2352678258

THE DISTRIBUTION,DEVELOPMENT AND EXPECTATION OF SHALE GAS RESOURCES

2010· article· en· W2352678258 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResources and Industries · 2010
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsnot available
Fundersnot available
KeywordsShale gasOil shaleChinaNatural gasGeologyGovernment (linguistics)Natural resourcePetroleum engineeringUnconventional oilBusinessNatural resource economicsMining engineeringGeochemistryGeographyPaleontologyPolitical scienceEconomicsWaste managementEngineeringArchaeology
DOInot available

Abstract

fetched live from OpenAlex

The exploration of shale gas resources becomes a focus of the world.The natural gas resources are 636.283×1012 m3 in the world.Shale gas resources are rich in America,most of them are distributed in southern,central and eastern parts.There also are plenty of shale gas resources in China,nearly the same quantity as in America.In America there is the most advanced exploration and exploitation technology,and it is the only country which has the highest exploitation method.Canada has a long history of shale gas exploration and exploitation.China is still at the beginning for the shale gas exploitation.The permeability of the shale rocks is normally very low,so it is difficult to be exploited.Therefore,we need to learn the advanced foreign technology to develop a set of exploitation methods to develop our shale gas reservoirs,and we need the support from the government,increasing environmental protection while 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.

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 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 score0.920
Threshold uncertainty score0.167

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 science0.0000.000
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 head0.009
GPT teacher head0.180
Teacher spread0.171 · 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