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Record W4306173614 · doi:10.1038/s41597-022-01737-0

OSeMOSYS Global, an open-source, open data global electricity system model generator

2022· article· en· W4306173614 on OpenAlexafffund
Trevor Barnes, Abhishek Shivakumar, Maarten Brinkerink, Taco Niet

Bibliographic record

VenueScientific Data · 2022
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity College CorkLoughborough UniversityImperial College LondonScience Foundation IrelandGovernment of CanadaGovernment of the United KingdomForeign, Commonwealth and Development OfficeColorado School of Mines
KeywordsOpen sourceOpen dataElectricityOpen system (computing)Computer scienceGenerator (circuit theory)Electricity systemWorld Wide WebElectricity generationOperating systemEngineeringElectrical engineeringSoftwarePhysicsPower (physics)

Abstract

fetched live from OpenAlex

This paper describes OSeMOSYS Global, an open-source, open-data model generator for creating global electricity system models for an active global modelling community. This version of the model generator is freely available and can be used to create interconnected electricity system models for both the entire globe and for any geographically diverse subset of the globe. Compared to other existing global models, OSeMOSYS Global allows for full user flexibility in determining the time slice structure and geographic scope of the model and datasets, and is built using the widely used fully open-source OSeMOSYS energy system model. This paper describes the data sources, structure and use of OSeMOSYS Global, and provides illustrative workflow results.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0310.013

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 head0.067
GPT teacher head0.295
Teacher spread0.227 · 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.

Study designSimulation or modeling
Domainnot available
GenreSoftware

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

Citations49
Published2022
Admission routes2
Has abstractyes

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