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Record W2368323063

Analysis on Application of The Repast System Simulation Platform for Geography

2012· article· en· W2368323063 on OpenAlexaff
Guoyi Wang

Bibliographic record

VenueGround Water · 2012
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Computational Techniques and Applications
Canadian institutionsScience North
Fundersnot available
KeywordsSoftware portabilityScalabilityComputer scienceFrame (networking)GeographerComplex adaptive systemSystems engineeringSoftware engineeringDistributed computingEngineeringGeographyDatabaseOperating systemArtificial intelligenceCartographyTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

The CAS theory based on the system simulation is one of the hot areas of research over the home country in recent years.The model building on computer to simulation is a basic method for the study of the complex systems.The Repast simulation platform is a popular one.By introducing the Repast background,it analyzes its frame structure,features and operation mechanism.The platform has strong with portability and scalability and is facilitated research and exploration based on application of Agent Modeling and Simulation of complex adaptive systems,and provides new ideas for study of complex adaptive systems.The article is based on application of the Geographer at home and discusses the prospect of Repast simulation platform in Geography.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.147

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2012
Admission routes1
Has abstractyes

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