MétaCan
Menu
Back to cohort
Record W2833362999 · doi:10.5539/esr.v7n2p79

Characteristics of Mudstone in Complex Fluvial Sedimentary System in Bohai L Oilfield

2018· article· en· W2833362999 on OpenAlexvenueno aff
Kai Huang, Chunsheng Shen, Kai Kang, Libing Wang, Zhongbo Xu, Lin Li

Bibliographic record

VenueEarth Science Research · 2018
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFaciesGeologyFluvialBeddingSedimentary rockGeochemistryGeomorphologyCoringMineralogyPetrologyStructural basinDrillingMaterials science

Abstract

fetched live from OpenAlex

Bohai L oilfield develops a complex fluvial sedimentary system, which includes many types of fluvial sedimentary facies. Based on the coring well of oil field, the distribution characteristics of mudstone are analyzed, it is shown that the mudstone has similar internal structure and can be classified into four types according to its color: gray to grayish, variegated, brown to gray-brown and khaki, the assemblage has a large gray to grayish mudstone section, large gray to grayish mudstone intercalated thin layer sandstone, gray to grayish mudstone associated with variegated (brown) mudstone, grayish mudstone associated with lacustrine sand grain bedding sandstone, concomitant generation of large staggered bedding sandstone and grayish mudstone, mixed (gray-brown) mudstone associated with large staggered bedding sandstone, interaction between different colors of mudstone and sandstone and large interlaced sandstone intercalated with thin layer mudstone. The mudstone color is mainly gray and grayish, and very few oxidized mudstone is developed alone, which indicates that fluvial mudstone may be formed in the reductive environment in humid climate, and the fluvial mudstone in this area may be formed in the oxidizing environment, which is different from the general understanding of fluvial facies, the oxidation color is the result of the later transformation.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
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 head0.058
GPT teacher head0.339
Teacher spread0.281 · 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 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueEarth Science ResearchSame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207