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Record W2948158782 · doi:10.3968/10996

Development of Organic Soil Suitable for Biodiesel-Based Drilling Fluids

2019· article· en· W2948158782 on OpenAlexvenueno aff
Jun Yan

Bibliographic record

VenueAdvances in petroleum exploration and development · 2019
Typearticle
Languageen
FieldEngineering
TopicElectrokinetic Soil Remediation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsBiodieselDrilling fluidPetroleum engineeringDiesel fuelEnvironmental scienceBiodegradationDrillingWaste managementDrilling engineeringBiochemical engineeringEngineeringEcologyMechanical engineeringChemistry

Abstract

fetched live from OpenAlex

The oil-based drilling fluid system has the advantages of excellent lubricating performance, strong inhibitive ability, good sidewall stability and good temperature resistance, etc., however, which also has disadvantages of polluting the environment, easy to catch fire, and higher preparation cost, etc. In the development of biodiesel drilling fluid system, we no longer use diesel or crude oil, instead, it is replaced by biodiesel. Biodiesel also has better environmental friendliness, stronger biodegradability, higher safety performance and renewable advantage (Xin, 2005) while meeting specific requirements and achieving relevant performance. Biodiesel drilling fluid is more suitable for actual drilling operations for the more fragile ecology and higher demand environment. However, the organic soil on the market is basically developed for the white oil system. Therefore, we developed organic soil suitable for biodiesel systems by combining the actual situation of organic soil in the market through the measures of comparison, optimization, modification, etc.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.599
Threshold uncertainty score0.617

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 head0.011
GPT teacher head0.232
Teacher spread0.220 · 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
Published2019
Admission routes1
Has abstractyes

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