MétaCan
Menu
Back to cohort
Record W2613203789 · doi:10.15802/stp2017/99952

CREATION OF EXPORT-ORIENTED NETWORK OF GRAIN ELEVATORS IN UKRAINE

2017· article· en· W2613203789 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScience and Transport Progress · 2017
Typearticle
Languageen
FieldEngineering
TopicTransport and Logistics Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsRouting (electronic design automation)ElevatorUkrainianOriginalityOperations researchGenetic algorithmComputer scienceMathematical optimizationBusinessTransport engineeringEngineeringMathematicsStructural engineeringComputer network

Abstract

fetched live from OpenAlex

Purpose. The scientific paper highlights improving the efficiency of export rail transportation of grain cargoes in Ukraine by introducing shipper routing and concentration of loading at the terminal grain elevators. Methodology. According to the experience of the USA and Canada, one of the most effective ways to reduce costs in the grain to-port supply chain is a shipper routing of the rail traffic. Shipper routing for transportation of grain cargoes involves the concentration of their loading on the multiple junctions. The junctions are proposed to be selected with the use of cluster analysis methods. For the formation of the grain loading concentration areas the authors used methods of set theory and multi-criteria optimization. Findings. Based on agglomerative cluster analysis algorithm, the junctions on a network of Ukrainian railways are selected and the areas of possible concentration of grain loading are formed. DSU-algorithm allowed distinguishing the overlapping and non-overlapping areas of concentration. The problem of selecting non-overlapping areas of the grain loading concentration is formalized as the problem of multiobjective integer programming with boolean variables. The solution of this problem by a modified simplex algorithm allows selecting on the railway network of Ukraine 24 districts of possible grain loading concentration, which cover 70 stations and at minimal additional cost provide routing of about 7.5 million tons of grain per year. Originality. The originality of the work lies in the fact that the authors developed the mathematical procedure for selection of junctions and concentration areas of grain loading at the Ukrainian railway network, taking into account the economic efficiency of the process. Practicalvalue. Application of the developed method of grain loading concentration for the formation of unit trains will significantly reduce the logistics costs in the supply chain of grain to Ukrainian ports for export and, consequently, increase its competitiveness in foreign markets.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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