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Record W2904746360 · doi:10.1063/1.5083572

Analysis of physico-chemical properties and territorial location of vanadium oils

2018· article· en· W2904746360 on OpenAlexaboutno aff
I. G. Yashchenko, Yu.M. Polishchuk

Bibliographic record

VenueAIP conference proceedings · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsVanadiumPetroleumChemical compositionFossil fuelGeologyCrude oilEnvironmental scienceGeochemistryChemistryPetroleum engineeringOrganic chemistryPaleontology

Abstract

fetched live from OpenAlex

The results of a study of the physicochemical properties of Vanadium oils and the regularities of their territorial distribution are presented. The information basis for the research was the database on the physicochemical properties of world oils, created at the Institute of Petroleum Chemistry of the SB RAS. It is established that Vanadium oils are found in 33 oil and gas basins of the world on different continents. The largest reserves of vanadium oils are in the West Canadian, West Siberian and Persian Gulf basins. It is shown that, on average, vanadium oils are heavy and viscous and highly viscous. According to their chemical composition, these oils belong to sulphurous, high-pitch and medium-paraffinic oils. Features of the geographical location of hard-to-recover oils of each of the oil quality classes were identified on base of using the tools of geoinformation system. As a result of analysis created map-schemes of placement of oil-gas-bearing basins of Vanadium oils location in the World.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.038
GPT teacher head0.214
Teacher spread0.176 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

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