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Record W2361326993

Views on gravomagnetic and electric exploration in Kuqa foreland basin

2003· article· en· W2361326993 on OpenAlexaff
Zeng Qing-quan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsGeologyForeland basinStructural basinTerrainHydrocarbon explorationStage (stratigraphy)Sedimentary basinMagnetotelluricsPaleontologySedimentary rockMining engineeringGeomorphologySeismologyCartography
DOInot available

Abstract

fetched live from OpenAlex

The Kuqa foreland basin is located in the west of China.It has experienced two stages of gravomagnetic and electric exploration.The first stage of reconnaissance was conducted in the 1950s.The object was to deal with the regional geological problem,such as the depression-uplift division,the distribution of faults and the thickness of sedimentary rock,as well as to provide the prerequisite for the subsequent seismic survey.In the 1990s,the second stage of detailed gravomagnetic and electric survey was carried out.A few seismic surveys were performed.Some exploration wells were drilled,and oil and gas shows were found.In combination with seismic data,the mountain,mountain front,deep-seated strata,salt and sub-salt and local structures were depicted,and the exploration targets were evaluated.The research was focused on the problem that seismic data could not reveal clearly.Fruitful achievements have been obtained during all the segments of the two stages.The geological tasks,technical competence and measurement precision involved in the first stage were much different from the second one.The combination of gravomagnetic technique with the seismic methods made it possible to achieve satisfactory results in the comprehensive understanding of mountainous area and mountain front under the complex terrain and geologic settings on surface and subsurface with the aid of mutual complement of multiple disciplines and a variety of information.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.765

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)0.0010.000

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 head0.030
GPT teacher head0.199
Teacher spread0.170 · 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 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

Citations1
Published2003
Admission routes1
Has abstractyes

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