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Record W4367848491 · doi:10.1190/int-2023-0006.1

Destruction mechanism of organic matter enrichment controlled by tectonism in the lower Silurian organic-rich marine mudstone in the western South China Block

2023· article· en· W4367848491 on OpenAlexaff
Tong Sun, Yiqing Zhu, Bo Ran, Ke Liang, Chao Luo, Yuyue Han

Bibliographic record

VenueInterpretation · 2023
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsPetro-Canada
FundersNational Natural Science Foundation of China
KeywordsLaminationSedimentologySedimentary depositional environmentGeologyOrganic matterSedimentary rockPalaeogeographyPaleontologyPetrographyGeochemistryTectonicsEcologyChemistry

Abstract

fetched live from OpenAlex

Abstract This destruction mechanism of organic matter enrichment plays an important role in improving the mudstone sedimentary structure system. For the lower Silurian marine mudstone in the western South China Block, the destruction mechanism of organic matter enrichment is unclear, with previous studies ignoring the control from paleogeography and spatial differences. Lamination is a typical sedimentary structure in mudstone and different types of lamination in mudstones can reflect a range of depositional environments. Lenticular lamination, composed of arranged lenses of variable composition, is a common type of lamination in marine mudstone and mainly occurs in organic-lean mudstone. The origin of lenticular lamination remains controversial, and a multidisciplinary approach is needed that integrates sedimentology, petrography, and paleogeography. The main objectives of this approach are to (1) interpret the formation mechanism of lenticular laminations in the Longmaxi marine mudstone, and (2) discuss the significance of lenticular lamination to organic matter destruction. The results not only allow for a complete understanding of the destruction mechanisms of the Silurian marine mudstones but also provide new insights into the sedimentary processes of marine mudstone.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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 designSimulation or modeling
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
Published2023
Admission routes1
Has abstractyes

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