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Record W2883025455 · doi:10.1134/s0965544118050067

Water-Soluble Complexes Catalyzed Coupling Aquathermolysis of Water-Heavy Oil-Methanol at Low Temperature

2018· article· en· W2883025455 on OpenAlexaff
Qiang Deng, Yongfei Li, Gang Chen, Yan Jiao, Jie Zhang, Mei Meng, Chengtun Qu, Ayodeji Jeje

Bibliographic record

VenuePetroleum Chemistry · 2018
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersNational Science Foundation
KeywordsCatalysisMethanolChemistryViscosityDecompositionMetalChlorideInorganic chemistryChemical engineeringOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

A series of complex was synthesized using phenyl hydroxamic acid and metallic chloride, and used for catalytic aquathermolysis of heavy oil at low temperatures for the first time. The effects of water content and catalyst concentration on aquathermolysis were investigated. And then a tri-component coupling aquathermolysis of water-heavy oil-methanol was designed and the reaction conditions were investigated. With the catalyst and methanol, the reaction occurred at temperatures as low as 180°C. The viscosity of the product was also substantially reduced by the decomposition of the large hydrocarbon molecules.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.008
GPT teacher head0.225
Teacher spread0.217 · 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.

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

Citations13
Published2018
Admission routes1
Has abstractyes

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