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Record W7006919833

Аналіз критеріїв, що впливають на вибір автозаправного комплексу

2017· article· uk· W7006919833 on OpenAlexaboutno aff

Bibliographic record

VenueElectronic Scientific Archive (Lviv Polytechnic) · 2017
Typearticle
Languageuk
FieldSocial Sciences
TopicEducation and Social Development in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsGasolineQuality (philosophy)Oil refineryMarket developmentMarket shareState (computer science)
DOInot available

Abstract

fetched live from OpenAlex

Розглянуто основні критерії, які впливають на вибір водієм автозаправної станції.
\nПодано детальну структуру автозаправного ринку України. Проаналізовано залежність якості палива від джерела його походження. Розглянуто ціну палива, зокрема у Львівській області. Подано кількісне розташування автозаправних станцій по усіх областях України та структуру послуг, пропонованих автозаправними комплексами. In the article the basic criteria that influence the driver`s choice of the petrol station are considered. The main criteria, that drivers give maximum evaluation to, are: the quality of fuel, the price of fuel, location of the petrol complex, loyalty programs offered by petrol complexes, offered services, additional services and promotions. The detailed structure of petrol market of Ukraine is presented, where 68 % of fueling market controls ten companies, namely the group of companies Privat, which is represented on the market under such brands as Avias, Ukrtatnafta, ANP, Maveks, Sentosa Oil, Yukon and others, WOG, OKKO, AMIS, BRSM-Nafta, Shell, TNK, SunOil, Market, Tarnett. The second largest participant at the fueling market of Ukraine is a network of Ukrnafta, which belongs to the state company “Naftogaz Ukraine”. Its share is 32 % of all petrol stations` market and it is represented by such brands as: ANP, AVIS, Ukrnafta, Sentora, Maveks and others. The dependence of a petrol quality from the source of origin is analyzed, despite the fact that the fuel at the petrol complexes in Ukraine comes both from Ukraine and abroad. Domestic refineries have high project capacity and optimal territorial location, but the volumes of refining annually fall. This leads to increasing supplies from abroad, namely Russia, Belarus, Greece, Poland, Lithuania, Israel, Romania and Bulgaria. The price of petrol, in particular A-95, in the Lviv region in 2011–2016 is considered, and determined that the maximum rates in UAH equivalent of all grades of petrol were installed in early February 2015. However, given the exchange rate of the euro, there were two peak periods: the first in June and July 2012, when prices were highest at the A-95, A-98 and LPG (gas); second in March 2015 for A-92 and diesel fuel. The quantitative location of petrol stations in all regions of Ukraine as well as their
\ngeographic concentration is presented. The structure of the services offered by filling complexes is presented; this structure is formed of four elements: the root of the services – the basic petrol station that offers only refiling, additional paid services, auxiliary paid services and useful free services.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0200.008
Scholarly communication0.0040.001
Open science0.0060.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.029
GPT teacher head0.340
Teacher spread0.311 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2017
Admission routes1
Has abstractyes

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